ES2762953T3 - System to provide personalized information and procedure to provide personalized information - Google Patents

Abstract

A computing device (100) comprising: a location finder (4311) configured to obtain location information from the computing device; a display system (4331) configured to display information indicating routes of the computing device; and a controller (4320) configured to: track the locations of the computing device (100) by determining that a location of the computing device (100) has changed based on the location information of the computing device (100) obtained by the browser (4311) location, obtain information corresponding to an initial route of the computing device (100) based on the tracked locations of the computing device (100), determine a predicted route of the computing device (100) based on the information corresponding to the route initial information of the computing device (100) and the past location information of the computing device (100), displaying the predicted route in the rendering system (4331) and controlling the location finder (4311) to track an actual location of the device (100 ) computing by varying a time interval for obtaining the location information of the computing device (100) based on It gives in at least one of the information of the surrounding environment of the computing device (100) and the planned route.

Description

DESCRIPTION

System to provide personalized information and procedure to provide personalized information

Technical field

One or more exemplary embodiments relate to a system for providing personalized information and a method of providing personalized information, and more particularly, to a system for providing personalized location-based information and a method thereof.

Background of the Art

With the development of communication techniques based on smart computing devices, location-based services to provide location-based information on a computing device are becoming popular.

Most current location-based services provide information based on the current location of a computing device. For example, if User A and User B run a mapping application using their respective computing devices at the same location and at the same time, the mapping application provides identical local information (eg famous places, information on events such as concerts or coupon information).

US 2008/318598 A1 refers to a handheld, portable navigation system and procedure that are integrated within a cell phone case, resulting in a simplified architecture with fewer push buttons and carry-on items. The device uses a cell phone that has a microphone, keyboard, GPS receiver, display system, memory, earpiece, wireless transceiver, and processor. The processor is programmed to receive a command through a user input device to determine the user's home location and activate the GPS receiver to obtain position coordinates associated with the home location. Coordinates are stored in memory. A subsequent command through a user input device causes the processor to determine the user's new location, and the GPS receiver is activated again to obtain position coordinates of the new location. The processor is further programmed to provide guidance to the user based on the coordinates of the starting location and the new location, allowing the user to return to the starting location from the new location. The user input device may be a wireless portable keyless entry device, such as a "key fob", in which case the processor is further operational to receive and store a DOOR LOCK vehicle command in memory and determine the location User initial when the phone receives and recognizes the DOOR LOCK command.

Disclosure of the invention

Technical problem

However, location-based services according to the related art consume a large amount of power from the battery of a computing device, and therefore it can be difficult to use the services continuously.

Solution to the problem

One or more exemplary embodiments include a system for providing personalized location-based information using information from the user's location history, whereby the power consumption of a computing device's battery is reduced, and a method of providing the personalized information based on at the location.

Additional aspects will be set forth in the description that follows and will be apparent from the description or may be learned by practicing exemplary embodiments.

Advantageous effects of the invention

In accordance with the above embodiments, it is possible to provide personalized location-based information that reduces the battery power consumption of a computing device.

Brief description of the drawings

These and / or other aspects will become apparent and will be more readily appreciated from the following description of exemplary embodiments, taken in conjunction with the accompanying drawings, in which:

FIG. 1 is a view illustrating an example of personalized information provided in accordance with an exemplary embodiment;

FIG. 2 is an operational flow chart of a method of providing personalized information in accordance with an exemplary embodiment;

Fig. 3 is an operational flow chart of a procedure for providing personalized information of in accordance with another exemplary embodiment;

FIG. 4 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

Fig. 5 illustrates an example of a screen for providing information of different interest based on the usage count information included in the information indicating a user's intended route;

FIG. 6 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

Fig. 7 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Fig. 8 illustrates an example of providing information about a region adjacent to a user's intended route, in accordance with another exemplary embodiment;

FIG. 9 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

FIG. 10 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Fig. 11 illustrates an example of providing information about a point of interest included in a region adjacent to a user's planned route, in accordance with another exemplary embodiment;

FIG. 12 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

Fig. 13 illustrates an example of providing information about a point of interest included in a region adjacent to a user's planned route, in accordance with another exemplary embodiment;

Fig. 14 illustrates an example of a screen including a list of search points of interest according to another exemplary embodiment;

FIG. 15 is an operational flow diagram of a method of providing personalized information in accordance with another exemplary embodiment;

Fig. 16a illustrates an example of a screen for providing information about a point of interest based on a current point on a user's planned route, in accordance with another exemplary embodiment;

Fig. 16b illustrates an example of a screen for providing information about a point of interest based on a destination point on a user's planned route, in accordance with another exemplary embodiment;

Fig. 16c illustrates an example of a screen for providing information about a point of interest based on a current point and a destination point on a user's planned route, in accordance with another exemplary embodiment; Fig. 17 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

FIG. 18 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

Fig. 19 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Fig. 20 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Fig. 21 illustrates examples of displays that can be provided according to an exemplary flow diagram of Fig. 20;

Fig. 22 is a view illustrating a procedure for providing personalized information in accordance with an exemplary embodiment;

Fig. 23 is an operational flow chart of a procedure for providing personalized information in accordance with an exemplary embodiment;

Fig. 24 illustrates an example of a screen illustrating a request to generate content according to an exemplary embodiment;

Fig. 25 illustrates an example of a representation topic article rendering system according to an example of

realization;

Fig. 26 illustrates an example of a screen including an input window through which new content is generated in accordance with an exemplary embodiment;

Fig. 27 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Figs. 28a and 28b illustrate examples of a system for rendering a recommendation topic article as a notification;

FIG. 29 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

Fig. 30 illustrates an example of a screen by which the exchange of generated content can be established, according to another exemplary embodiment;

Fig. 31 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Fig. 32 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Fig. 33 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

FIG. 34 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

FIG. 35 is a view illustrating a procedure for providing personalized information in accordance with another exemplary embodiment;

FIG. 36 is an operational flow chart of a method of providing personalized information in accordance with another exemplary embodiment;

Fig. 37 illustrates an example of a screen for selecting a subject item according to another exemplary embodiment;

Fig. 38 illustrates an example of a screen for setting a topic article filtering condition according to another exemplary embodiment;

Fig. 39 illustrates an example of a map image, in which a subject item according to another exemplary embodiment is marked at a point of interest;

Fig. 40 illustrates an example of a screen on which an augmented reality (AR) image and data about a point of interest are synthesized, according to another exemplary embodiment;

Fig. 41 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Fig. 42 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment;

Figs. 43 and 44 are functional block diagrams of a computing device in accordance with one or more exemplary embodiments; and

Fig. 45 is a structural diagram illustrating a system for providing personalized information in accordance with an exemplary embodiment.

Best Mode for Carrying Out the Invention

In accordance with one aspect of an exemplary embodiment, a computing device is provided including: a location finder configured to obtain location information from a user of the computing device; a rendering system configured to display information indicating a user path of the computing device; and a controller configured to: track a user's location upon detecting a change in the user's location based on location information obtained from the user, obtain information corresponding to a user's initial route based on the user's tracked location, determine a the user's expected route based on the information corresponding to the user's initial route and the user's past location information, and displaying the expected route in the rendering system.

After displaying the intended route in the rendering system, the controller can further be configured to: control the location finder to track a user route by varying a user location measurement interval based on at least one of the speed of user movement, information of the user's surrounding environment and expected route, and updating the user's past location information based on the user's traced route.

The controller may be further configured to control the location finder to obtain the initial route by varying a user location measurement interval based on at least one of the user's movement speed and information from the user's surrounding environment.

If the intended route is not determined from the user's past location information based on the initial route, the controller may further be configured to control the location finder to track the user's route by varying a location measurement interval of the user based on at least one of the movement speed and information of the user's surrounding environment, and updating the user's past location information based on the user's traced route.

The controller can also be configured to display personalized information about the user in the rendering system based on the intended route and user profile information.

The controller can also be configured to display recommendation information in the rendering system that includes at least one article of recommended content based on profile information from a location adjacent to the intended route and user profile information.

Recommended content may include a topic article.

The controller can also be configured to provide the recommended content in the form of a map or notification.

The controller may also be configured to detect regional information about a region adjacent to the intended route, in which regional information includes information about where a group of people is currently active and displays the regional information detected in the rendering system. .

The controller can also be configured to detect a user usage count on the intended route from the user's past location information, and display custom information in the rendering system based on the detected usage count.

In accordance with an aspect of another exemplary embodiment, there is provided a method of providing personalized information, performed by a computing device, including the method: obtaining information about a user's initial route by tracking a user's location upon detecting a change in the user location; determining a user's intended route based on information corresponding to the user's initial route and the user's past location information; and show the planned route in a computer device representation system.

The method may further include, after displaying the intended route in the rendering system, tracing a user route by varying a user location measurement interval based on at least one of a user's movement speed, information from the surrounding environment of the user and the planned route; and update the user's past location information based on the user's tracked path.

Obtaining information about the user's initial route may include obtaining information about the user's initial route while varying a measurement interval of the user's location based on at least one of the user's movement speed and the information from the user's surrounding environment.

If the intended route is not determined from the user's past location information based on the user's initial route, the procedure may include: tracking the user's route by varying a measurement interval of the user's location based on the minus one of the user's movement speed and information from the user's surrounding environment; and update the user's past location information based on the user's tracked path.

The procedure may further include providing personalized information about the user based on the intended route and user profile information.

Providing personalized user information may include providing recommendation information that includes at least one recommended content article based on profile information from a location adjacent to the intended route and user profile information.

Recommended content may include a topic article.

The procedure may further include providing the recommended content in the form of a map or notification.

Provision of personalized user information may include: detecting regional information about a region adjacent to the intended route in which regional information includes information about where a group of people is currently active; and provide the detected regional information.

The method may further include detecting a user usage count on the intended route from the user's past location information, and providing the customized information according to the detected usage count.

In accordance with an aspect of another exemplary embodiment, a computing device is provided including: a location tracker configured to track a location of the computing device; a memory configured to store a location history of the computing device according to the tracked locations; a controller configured to determine a starting path of the computing device by comparing a current location of the computing device with a previous location of the computing device, and determining a predicted path of the computing device based on the initial path and location history of the computing device.

The controller can be further configured to detect information corresponding to a point of interest based on a point in the intended path of the computing device, and display the information corresponding to the point of interest in a computing device display system.

The location tracker can include a sensor.

The controller can further be configured to control a rendering system to provide a menu of theme articles to a user, and receive input from the user to select a preferred theme article.

The driver can also be configured to determine a recommended topic article based on a point of interest near the intended path of the computing device and the user's preferred topic.

In accordance with an aspect of another exemplary embodiment, a non-transient computer-readable recording medium is provided that stores one or more programs that includes commands to execute a procedure of providing custom information, in which the procedure is performed in the same manner. The procedure described above is performed to provide personalized information.

Mode for the invention

Reference will now be made in detail to one or more exemplary embodiments, the examples of which are illustrated in the accompanying drawings, in which like reference numerals refer to like elements throughout. In this regard, exemplary embodiments may have different shapes and should not be construed as limited to the descriptions set forth herein. Accordingly, exemplary embodiments are simply described below, with reference to the figures, to explain aspects of the disclosure. As used herein, the term "and / or" includes any and all combinations of one or more of the associated numbered items. Expressions such as "at least one of", when preceding a list of items, modify the entire list of items and do not modify the individual items in the list, unless specifically stated otherwise.

However, disclosure is not limited to particular modes of practice, and it should be appreciated that all changes, equivalents, and substitutes that do not depart from the spirit and technical scope of inventive concepts are included in disclosure. In the description of inventive concepts, certain detailed explanations of the related art may be omitted if it is considered that they may unnecessarily obscure the essence of the inventive concepts.

While terms such as "first" "second", etc., can be used to describe various components, those components are not limited to the above terms. The above terms are used only to distinguish one component from another.

The terms used in this disclosure may be broad terms widely used in the art in consideration of functions with respect to inventive concepts, but the terms may vary according to the intent of those skilled in the art, precedents, or new technologies in The technique. Furthermore, the applicant can select the specified terms and, in this case, the detailed meaning thereof will be described in the disclosure. Thus, the terms used in the specification are to be understood not as simple names but based on the meaning of the terms and the general disclosure.

An expression used in the singular encompasses the expression in the plural, unless it has a clearly different meaning in context. In the present specification, terms such as "including", "comprising", or "having", etc., should be understood as intended to indicate the existence of the characteristics, numbers, stages, actions, components, parts, or Combinations thereof disclosed in the specification, and are not intended to exclude the possibility that one or more other characteristics, numbers, stages, actions, components, parts, or combinations thereof may exist or may be added.

The term user location history information in the specification can refer to cumulative information about points and places a user has been, starting from a particular time, (for example, once a user accepted the terms of a service through a computing device) until now. A service may refer to a service to collect location information from a user or a service to provide personalized information according to an exemplary embodiment.

The service can run continuously while power is supplied to a computing device, and the service can run regardless of whether the computing device is being used. However, the service is not limited to this. For example, the service can be run according to an environmental condition set by a user. The environmental condition can be established according to location and / or time. For example, the environmental condition can be set such that a service is run when the computing device is in a location other than a user's home or office. The environmental condition can be set in such a way that the execution of a service is stopped according to the user's request to stop the service.

User location history information may include, without limits, at least one of a user mode (eg Stay, Walk or Drive), an indoor / outdoor mode (eg Indoor or Outdoor), a providing location information (for example, Network Provider, Global Positioning System (GPS) Provider, or Sensor), a latitude value, a longitude value, altitude value, a support value, precision, and time.

If a latitude value or longitude value included in the user location history information is a filtered value, the user location history information may also include an original latitude value and an original longitude value. The original latitude value and the original longitude value are unfiltered values. Filtering with respect to a latitude value and a longitude value can be performed using, but not limited to, a Kalman filter, i.e. linear quadratic estimation (LQE).

The user's location history information may also include information about the content (for example, an image, a note, a video, a topic article, and / or a recommendation message).

The network provider included in the location information delivery mode may include at least one Wi-Fi communication, cellular identification communication, near field communication (NFC) and Bluetooth beacon communication, but is not limited to the same. The sensor included in the location information delivery mode may include, but is not limited to, a light emitting diode (LED) sensor, a geomagnetic sensor, an accelerometer sensor, and / or a gyroscope sensor.

"Driving" included in the user mode can be expressed as a means of transport such as a car, a bicycle, bus, train, plane, boat or helicopter. User mode can be expressed as a user activity. User activity represents a particular user action. For example, user activity may include, without limits, at least one of walking, walking, running, exercising, cooking, cleaning, sleeping, seeing a friend, eating, going to work, and / or coming home from work. .

User activity can be expressed as one of an icon, a text, an image, and a multimedia. User activity may be classified as Life, Eating, Drinking, Entertainment, Sports, and / or Work, but the user activity classification standards are not limited thereto.

A user activity item included in "Life" may include, for example, unlimited, cooking, cleaning, resting, walking, walking, meeting, talking, shopping, beauty, dating, driving, pets, birthdays, weddings and / or events.

A user activity item included in "Eat" can include, for example, unlimited, Korean food, Western food, Chinese food, Japanese food, Thai food, Italian food, Indian food, snacks, fast food, bread, fruit and / or vegetables.

A user activity item included in "Drinking" may include, for example, unlimited, water, milk drink, coffee, tea, juice, soda, alcohol, hot drink, cold drink and / or functional drink.

A user activity item included in "Entertainment" may include, for example, unlimited, at least one of reading, writing (or notes), playing, watching a movie, listening to music, singing, dancing, TV, exposure, shows , festival, picnic, camping, photography, gardening, fishing, meditation and / or volunteering.

A user activity item included in "Sports" may include, for example, unlimited, at least one of running, cycling, hiking, baseball, basketball, football, soccer, martial arts, extreme sports, yoga, fitness, leisure, swimming, diving, skiing, snowboarding and / or skating.

A user activity item included in "Work" may include, for example, unlimited, at least one meeting, presentation, conference call, seminar, education, workshop, conference, promotion, business trip and / or work out.

Information (eg profile) about a user's past path (eg path) can be generated based on machine learning about the user's location history information. The user's past path may refer to a path based on a user's movement generated prior to a user's movement related to the current location of a computing device, after accepting a service using the computing device.

Information about the user's past route may include, without limits, information about at least one of a starting point, a destination point, a point and / or place where a user has stayed, the location of a tracked user , a time when a user's location is tracked, a movement start time, a movement end time, a total movement time, a movement time for the respective user modes, a movement speed for the respective user modes, number of times to use a route, number of times to visit a destination point and / or information about the content.

Information (or profile) about a user's primary route or major route can be generated by machine learning about the user's location history information. A user's primary path can refer to at least one path that is traveled the most times, out of a user's paths, generated before a user's path related to the current location of a computing device, after accept a service using the computing device.

Information about a user's primary route may include, without limits, information about at least one of a starting point, a destination point, a point and / or place where a user has stayed, the tracked position of a user (or user location), once a user's position is tracked, a movement start time, a movement end time, a total movement time, a movement time for the respective user modes , a movement speed for the respective user modes, the number of times a route is used, the number of times it visits a destination point and / or information about the content.

Information (or profile) about a region that a user has usually stayed in and about a user's activity in the region that the user has usually stayed in can be generated through machine learning about location history information of the user. The region in which the user has usually resided may include, without limits, a house, an office, a school and / or an educational institution.

Machine learning about user location history information can be performed using a device that stores user location history information.

The user's location history information can be stored on at least one of a computing device, a device designated as a user's personal cloud (for example, a home sync, an Internet of Things network-based device ( IoT) (for example, a smart television), a hand, another computing device, and a server, etc.), and / or a device within an area where a user can directly control the device. The user's location history information may be stored at a service provider with the user's consent.

When machine learning about user location history information is unsupervised learning, user location history information can be grouped to automatically extract distribution characteristics (or properties such as time) contained in the location history information. user location, and not only the information described above can be generated, but also a custom profile or model based on a user location based on the extracted distribution characteristics. Machine learning about user location history information can be done as, but not limited to unsupervised learning or supervised learning.

Information from the user's location history can be collected at predetermined intervals, for example, fixed period. For example, user location history information can be collected once every minute, for a total of 1,440 entries. The 1440 inputs can include, without limits, at least one of a user mode, an indoor / outdoor mode, a way to provide location information, a latitude value, a longitude value, an altitude value, a value of support, a precision and / or time value described above.

The user's location history information may be collected for a variable period according to at least one of a user's movement speed, information about a user's surrounding environment and / or a user's past path. When user location history information is collected for a variable period, the number of entries included in the user location history information collected per day may be random. The information included in the user location history information entries collected for a variable period may be the same as the information included in the user location history information entries collected for a fixed period described above.

A user described throughout the specification may refer to a person who has a computing device. In this way, the movement of the user can represent the movement of the computing device. A user path can represent a path from the computing device. Tracking a user's position may refer to tracking a position of the computing device. The initial path of a user can represent an initial path of the computing device. A user's intended path can represent a planned path of the computing device. Information from the user's surrounding environment may represent information from the surrounding environment of the computing device.

The context information described throughout the specification may include, without limitation, at least one of user-based context information and / or geographic location-based context information.

User-based context information may include information about a user mode, a user's movement speed, a user's movement time, a distance a user has traveled, and / or a location to which he has moved. the user, described above.

The speed of movement of a user can be continuously measured after starting to use a computing device, but is not limited thereto. For example, a movement speed can be continuously measured from when the user movement has started until when the user movement stops. A movement speed can be measured in a previously established time interval and / or a previously established distance interval.

The movement time of a user can include, but is not limited to, the total movement time a user moves per day. For example, a user's movement time can include the times the user starts and stops moving. The movement time of a user can include a total movement time for the respective user modes. The user's movement time can include the times the user starts and stops moving for the respective user modes.

A user's movement distance may include, but is not limited to, the total movement distance the user travels per day. For example, a user's movement distance may include the total movement distance for the respective user modes.

Information indicating a location to which a user has moved may include, but is not limited to, latitude and longitude. The information indicating a location a user has moved to may further include an indoor / outdoor mode, a way to provide location information, an altitude value, a support value, and a precision value. Information indicating a location the user has moved to can also include the name of a place. The precision value can represent as a range of error with respect to a user's current location.

User-based context information can include information about a user's current location and weather related to the user's current location. Information about the user's current location may include, but is not limited to, a latitude value and a longitude value. For example, information about the user's current location may further include an indoor / outdoor mode, a way to provide information about location, an altitude value, a support value and / or a precision value. Information about the user's current location may also include the name of a place. The name of a place can be expressed as, but is not limited to, for example, home, office, restaurant, store, business, school, educational institution and / or park. The time related to the user's current location may include, but is not limited to, a current time. For example, if a user mode is Stay, the time related to a current location can include the duration (for example, start time and end time) for which the user remains in a location.

User-based context information can include information about a user. User information may include, without limitation, at least one of user profile information, user health information (eg, heart rate, blood flow, breathing rate, and / or skin temperature), information about the user's emotion (for example, joy, grief, fear, anger, surprise, gratitude, and hatred), and information about the user's schedule (for example, wedding, meeting, and meeting).

User information may include information about user-generated content in one place. Information about user-generated content may include, without limit, user-generated content in store B at train station A, a type of generated content (for example, a document, an image, an audio, or a video), one topic article of the generated content and / or the amount of content generated for each topic article. Information about user-generated content can be included in the content history information. When user-generated content is published on social media, information about user-generated content may be included in a history of social media services.

User information may include information about a topic article preferred by a user.

User information can include, without limits, at least one of a search history, an email history, a message history (for example, a history of short text messages, a history of multiple messages and / or a voicemail history), a browsing history, and a history of social networking services.

Search history, mail history, message history, browsing history, and history of social networking services or the like may include, respectively, without limitation, information generated by an interaction between a user and a computing device while at least one of a search application, a mail application, a message application, a navigation application and a social networking service application, or the like, installed on the computing device are executed. The information generated by the interaction between the user and the computing device may include, for example, a list of search keywords, a list of transmitted and received emails, a list of transmitted or received messages, a list of uniform resource locators (URL) and / or information on the result of the analysis of input and output data.

A search history, email history, message history, browsing history, and history of social networking services can be based on, without limits, detection of at least one of a keyword, an image, a place, a time and event (for example, a baseball game, a soccer game, a concert or a play, etc.) through at least one of context analysis, vocabulary analysis, image analysis, and / or or tag analysis.

User information can include, without limits, at least one information about at least one person who shares a social connection with the user (for example, a friend on Facebook), at least one person registered in a user's phone book and the content generated by the at least one person, information about a topic article preferred by the at least one person, information about a profile of the at least one person, information about a profile of at least one person who is with the user , information about content generated by at least one person who is with the user, information, information about a topic article preferred by at least one person who is with the user, information about at least one person who shares a destination point with the user. user, an activity of the at least one person and / or a topic article of the at least one person. The activity of the at least one person can be expressed in a similar way to the user activity described above.

User profile information may include, without limits, information on gender, age, interest, a point of interest (POI), a preferred POI, preference, hobby, current residential area, place of birth, work, and / or a office location. For example, user profile information may include profile information from social networks on social networks (for example, Facebook, Twitter, blog, YouTube or LinkedIn).

The information of the profile of social networks can be configured by detecting at least one of a keyword, an image, a place, a time and an event by analyzing at least one of a text, a word, an image and / or a published tag by a user, but is not limited to them. The profile information of at least one person related to a user can be configured as the user profile information described above.

Information about a user may include at least one information from the Personal Information Management Software (PIMS) and / or life record information.

Information about a user may include information from the user's surrounding environment. Information from the surrounding environment may include an indoor / outdoor mode, Wi-Fi access point information (eg, a fingerprint digital of a Wi-Fi access point), illuminance and / or a cellular identification, but not limited to them. Information from the surrounding environment may include information used to determine whether a user is indoors or outdoors. Information from the surrounding environment may include values detected by an IoT network based sensor (hereinafter referred to as an IoT sensor) that is located around a computing device. The IoT sensor can include, without limits, at least one of a temperature sensor, a humidity sensor, an atmospheric sensor, a sunlight quantity sensor, an ozone sensor, a yellow sand sensor, a dust sensor , a carbon dioxide sensor, a gas sensor and / or a fire sensor.

Information about a user can be obtained using a computing device based on data that is generated or input or output through the interaction between a computing device and a user. Information about a user can be directly entered, edited, reviewed or deleted by a user. Information about a user can be provided by an external device of a computing device. The external device may include, for example, a handheld device such as a smart watch, glasses, an application accessory, and / or a server (eg, a social media service server).

Contextual information based on geographic location can be expressed as information based on geographic location. Contextual information based on geographic location may include, but is not limited to, location profile information. Place profile information may include, without limits, at least one of a place name (for example, Gwanghwa-mun), a place address, a store name (for example, Seoul Bibimbap), information about content generated on-site, an event occurring on-site (for example, a concert, a show, a photo exhibition, an art exhibition, advertising and / or discount coupons), weather, season, time, day , visitor information, the number of times the user visits the place and / or the floating population information of the place.

The location profile information may be collected by, but not limited to, a site server that provides location profile information (eg, a map server or a POI server). For example, location profile information may be provided by an application that provides location profile information installed on a computing device.

The application that provides place profile information may collect information about places while communicating with, but not limited to, the server that provides place profile information. For example, the application that provides location profile information may collect location information from an external device on a computing device. The application that provides location profile information can be updated by the server that provides location profile information. The application that provides place profile information can collect information about places by interacting with a user of the computing device.

The location profile information may be different depending on at least one of a day of the week, time, weather and / or season. For example, the information about the content registered in place A (for example, a content type, a topic article or a content recommendation message) may be different depending on at least one day of the week, time, weather and / or season. The information about the content registered in place A on Monday may be different from the information about the content registered in place A on Tuesday. The information about the content registered in place A at 7 pm may be different from the information about the content registered in place A at 1 pm. Information about content recorded at location A on a rainy day may be different from information about content recorded at location A on a clear day. Information about content recorded at location A in spring may be different from information about content recorded at location A in winter.

The information about the content registered in location A may be different depending on the condition of combining a day of the week and the weather. The information about the content registered in place A may be different depending on the condition of combining a day of the week and the time. The information about the content registered in place A may be different depending on the condition of combining a day of the week and the season. The information about the content registered in place A may be different depending on the condition of combining a day of the week, weather and / or time. The information about the content registered in place A may be different depending on the condition of combining a day of the week, weather and / or season. The information about the content recorded at location A may be different depending on a combination of climate, time and / or season.

Information about content may be recorded differently according to different conditions than those described above. For example, information about content may differ from person to person. That is, the information about the content registered by user A at location A may be different from the information about the content registered by user B at location A.

The content information described throughout the specification may include, without limitation, a content type, content, a topic article corresponding to the content, the number of content pieces generated for each topic article, and a recommendation based on the content.

The topic article may indicate a representative activity of a user included in the content to be generated.

For example, the topic article may include at least one of, for example, unlimited, coffee, cycling, a meeting, dating, a movie (or watching a movie), driving, sports, shopping, a visit to the hospital (or a hospital), read, study, beauty care, eat, a game, a stay, hiking, go out all night, kill time, a tasty food restaurant, talk, wellness, travel, self-development, cook, rest, cleaning, a walk, a pet, a birthday, a show and / or a business trip.

The topic article can be set based on user input. The topic article can be configured when manufacturing a computing device. The topic article can be directly entered, edited, reviewed, deleted or added by a user. The theme article may be provided in the form of but not limited to an icon, text, image, and media. For example, the theme article can be expressed as an icon or a combination of an icon and text.

The topic article can be used when filtering a point of interest with respect to a user. The point of interest with respect to a user can indicate a personalized place for the user (for example, a café, a tasty restaurant, a park or a promenade).

Hereinafter, exemplary embodiments will now be described in more detail with reference to the accompanying drawings. Components that are the same receive the same reference number and redundant explanations can be omitted.

Fig. 1 is a view illustrating an example of personalized information provided in accordance with an exemplary embodiment. FIG. 1 illustrates an example of providing information about a user's predicted path (or a user's predicted path) based on information about a user's initial path (or initial path) tracked using a computing device 100.

Referring to FIG. 1, when the computing device 100 detects user movement at a point 101 illustrated on a screen 110, the computing device 100 tracks a user location to a current point 102 to obtain information about an initial route 103 of the user. Current item 102 may indicate a current location of the user having computing device 100. Hereinafter, point 101 will be referred to as starting point 101.

The information about the initial route 103 may include user location information measured between the starting point 101 and the current point 102 (for example, the coordinate information expressed by a latitude value and a longitude value) and a time at User location is measured but not limited to them. For example, information on initial route 103 may further include information on a user mode and / or information on user-generated content.

When the user's location is measured ten times between the starting point 101 and the current point 102, the information about the initial route 103 obtained using the computing device 100 may include ten entries. Each entry includes information about a point at which the user's location is measured.

Information about the point at which the user's location is measured may include information about the location of the user being measured and / or when the user's location is measured. Information about the point at which the user's location is measured may further include information about a user mode and information about user-generated content. The computing device 100 can generate an entry for each time the location of the user is measured.

Current point 102 can be determined based on, but is not limited to, a previously established movement distance and / or a previously established movement time. For example, current point 102 can be set according to a user input. User input may include, but is not limited to, a user input that indicates a request for personalized information (request for a planned route). User input can include, without limits, at least one of a touch input, a voice-based user input, and a gesture-based user input.

When information about the initial route 103 is obtained, the computing device 100 detects information about a user's planned route from the user's location history information based on the information about the initial route 103. The user's location history information can be expressed as a profile of the user's locations.

The profile of user locations can be generated by machine learning about information collected from user location history. The profile of the user's locations can be generated by using a device that stores the user's location history information. The user's location history information may be stored on, but is not limited to, the computing device 100. For example, the user's location history information can be stored on an external device previously designated by a user, such as a home sync.

The external device may be located outside of the computing device 100. The external device can be a device designated as the user's personal cloud (for example, a home sync, a device based on the loT network (eg, a smart TV, hereinafter referred to as a loT device), a handheld device, another computing device, or a server), and / or a device within an area to be controlled directly by the user.

The external device that stores the user's location history information can collect information from the user's location history for a predetermined period of time using the computing device 100. For example, a home sync may collect information from the user's location history using computing device 100. The user's location history information can be collected for a predetermined period of time using the computing device 100.

By collecting the user's location history information, the computing device 100 or the external device can measure the location of a user using a user location tracking procedure performed in step S202 of Fig. 2 which will be described later. , but is not limited to them.

For example, computing device 100 detects a route similar to a current route from cumulative route information or past route information. The computing device 100 can measure the location of a user by determining a next location measurement point based on the detected similar path. A user's next location measurement point can be determined based on a similar route by considering the user's deviation to another route. For example, computing device 100 may determine a measurement point of a user's location by considering a point at which a route branches, such as a forked road, an intersection, or a junction.

When the user's location history information is stored on the external device, the computing device 100 can detect information about a user's expected route by reading the user's location history information from the external device, but is not limited to themselves. For example, computing device 100 may provide the external device with information about the initial route 103, and request information indicating the user's expected route from the external device and receive it from the external device.

The computing device 100 may provide a user with information indicating the user's intended route. For example, as illustrated on a screen 120 in FIG. 1, the computing device 100 may provide the user with information about a user's intended route 104.

The computing device 100 can display the user's initial route 103 and the user's intended route 104 differently so that the user can intuitively distinguish the two. For example, as illustrated on screen 120 in FIG. 1, computing device 100 may display initial route 103 with a solid line, and the user's intended route 104 with a dotted line, but display of route 103 The initial and intended route 104 of the user is not limited to an exemplary embodiment of FIG. 1.

The computing device 100 may include, without limitation, for example, a portable device, a handheld device, an Internet appliance, or a mobile device.

The portable device example may include, without limitation, a smartphone, notebook, smart board, tablet-type personal computer (PC), handheld device, handheld computer, media player, e-book device or a personal digital assistant (PDA).

The handheld example may include, without limits, smart glasses, a smart watch, a smart band (eg, smart waist band, or smart hair band), various smart accessories (eg, smart ring) , smart bracelet, smart anklet, smart hairpin, smart clip and smart collar), various smart body protection pads (for example, smart knee pads, smart elbow protection pads), smart shoes, smart gloves, smart clothes, smart hats, a smart artificial leg, or a smart artificial hand.

The example of the Internet home appliance can include, without limits, a smart TV, a smart player, a smart frame, a smart oven, a desktop PC, a smart refrigerator, a smart washing machine, a smart lighting, a smart training machine , a smart dryer, a smart dishwasher, a smart bed, a smart wardrobe, or a smart crime-fighting system (for example, CCTV). The example of the Internet appliance may include a machine-to-machine (M2M) device or a home device based on the IoT network.

Examples of the mobile device may include, without limits, an M2M device or an IoT network based car, or a car navigation device.

Fig. 2 is an operational flow chart of a procedure for providing personalized information in accordance with an exemplary embodiment.

In step S201, computing device 100 detects if a user's location (or a user's position) moves. Detection of whether the user's location is moved can be indicated by detecting whether the user's location has changed. The computing device 100 can detect whether the user's location moves based on a value latitude and longitude value of computing device 100. For example, if one of the latitude and longitude values of computing device 100 is changed, computing device 100 may determine that the user's location is moved.

The latitude value and longitude value of computing device 100 can be provided from a network provider (or a provider of network location information) or can be detected from a signal received from a GPS satellite. The network provider may provide the latitude value and longitude value of the computing device 100 based on the address information of a current location (or a current position) of the computing device 100, but the method of providing the latitude value and the length value by the network provider is not limited thereto.

A procedure for detecting whether the user's location is moving is not limited to the procedure described above of using the latitude value and longitude value. For example, the computing device 100 can detect whether the user's location is moving based on the location information of a base station that is connected to the computing device 100 (eg, a cellular identification), a fingerprint of a point of Wi-Fi access that is connected to the computing device 100 and information from the surrounding environment (eg, a detection value (eg, visible beam illuminance) from an illuminance sensor (eg, an LED sensor) or a detection value from an IoT sensor).

The computing device 100 can detect whether the user's location is moving using an inertial navigation procedure using an accelerometer sensor and a gyroscope sensor included in the computing device 100, a magnetic field fingerprint procedure using an included geomagnetic sensor. in the computing device 100, or a method of detecting a signal generated through NFC or a Bluetooth beacon (Bluetooth signal generator).

Before detecting whether the user's location is moved, the computing device 100 can determine whether the user's current location is indoor or outdoor. For example, computing device 100 can determine whether a user's current location is indoors or outdoors based on a layout diagram of a GPS satellite. That is, the computing device 100 detects a distribution diagram of a GPS satellite based on a received GPS signal. When the detected distribution pattern of a GPS satellite is uniform, the computing device 100 can determine that a user's current location is in the open. When the detected distribution pattern of the GPS satellite is not uniform, the computing device 100 can determine that a user's current location is indoors.

The computing device 100 can determine a method of detecting whether the user's location is moving and a method of tracking the location of the user based on the result of determining whether the user's current location is interior or exterior. For example, when a user's current location is indoors, computing device 100 may determine one of the procedures for using a network and / or a sensor as a procedure for detecting whether the user's location is moving and a procedure for tracking the user location. For example, if a user's current location is outdoors, One of the procedures for using a network and / or a GPS can be determined as a procedure to detect if the user's location is moving and a procedure to track the location of the user. user.

By tracking the path of the user, the computing device 100 can determine a method of detecting whether the location of the user is moving and a method of tracking the location of the user in multiple ways. For example, computing device 100 can detect whether the user's location is moved using a sensor, and can track the user's location using a hybrid method in which both a network and a GPS are selectively used.

By tracking the user's path, the computing device 100 can vary a method of detecting whether the user's location is moving and a method of tracking the user's location based on at least one speed of movement of a user, information from the surrounding environment of the user and a past route (or a planned route of the user).

When movement of the user's location is detected, the computing device 100 tracks the user's location in step S202. The computing device 100 can continuously track the location of the user, but is not limited thereto. For example, computing device 100 can track the location of the user in a preset measurement range. The preset measurement interval can be set based on time and / or distance.

The preset measurement range can be set differently according to user mode. For example, a preset measurement interval used by a walking or running user may be different from the preset measurement interval of a user traveling in an automobile. Additionally, a predetermined measurement interval used when a user travels in an automobile may be different from a predetermined measurement interval used when a user travels in a boat.

By tracking the location of the user, the computing device 100 can variably control a user location measurement range based on at least one of a user movement speed and a information from the user's surrounding environment.

For example, if the user's movement speed increases, the computing device 100 may shorten a measurement range of the user's location. If the speed of movement of the user is reduced, the computing device 100 may increase a measurement range of the user's location.

An interval within which a user location measurement interval is variably controllable according to the user's movement speed may be different according to a user mode. For example, the range within which the user location measurement interval is variably controllable when a user walks or runs may be different from a range within which the user location measurement interval is variably controllable when a user travel in a car. The range within which a user location measurement range is variably controllable can be represented in the form of a maximum value and a minimum value.

Even if a large amount of user movement is detected, if it is determined based on information from the user's surrounding environment that the user stays in one location, the computing device 100 may increase a user location measurement range to that is longer than a previous user location measurement interval. User motion can be detected using a motion sensor included in computing device 100. The example of the motion sensor can include, without limits, an accelerometer sensor, a geomagnetic sensor and / or a gyroscope sensor.

Even if the user's movement speed is faster, if it is determined based on information from the user's surrounding environment that the user stays in one location (for example, if a user is rotating in one position or moving quickly in a point of the same Wi-Fi fingerprint), the computing device 100 may increase a user's location measurement interval to be longer than a previous user location measurement interval.

As described above, variably controlling a user location measurement interval or increasing a user location measurement interval to be longer than a previous user location measurement interval, or controlling a Indoor user location tracking procedure differently from an outdoor user location tracking procedure, the battery consumption of computing device 100 due to user location tracking can be reduced.

Tracking a user location using computing device 100 in step S202 can be performed as a function of, but is not limited to, a preset time and / or a preset distance.

Based on tracking the user's location performed at S202 using computing device 100, computing device 100 obtains information about a user's initial path in step S203. Information about an initial route is described above with reference to Fig. 1.

When the initial route information is obtained, the computing device 100 detects information indicating the user's expected route from the user's location history information based on the information about an initial route in step S204. The user's location history information can be stored on the computing device 100, but can also be stored on an external device on the computing device 100 as described with reference to FIG. 1.

When the user location history information is stored in an external device, the computing device 100 can read the user location history information stored in the external device in step S204 as described with reference to FIG. 1 and detect the information indicating the user's expected route from the read user's location history information, or you can request information indicating the user's expected route to the external device and receive it from the external device.

When the user's location history information is stored in the computing device 100 or read from an external device, the computing device 100 can detect the information indicating the user's intended route using a procedure described below.

The computing device 100 can detect information indicating the user's expected route using a statistical analysis procedure. Examples of information used to detect information indicating the user's predicted route may include, without limits, a location measurement time, a latitude value, or a longitude value. For example, the information used to detect information indicating the user's intended route may further include information about a user mode and / or information about user-generated content.

The computing device 100 can detect a user's route information by comparing information about an initial route and the user's location history information. Information about a user's route includes information about a route similar to an initial route.

The computing device 100 can detect information about the user's route, including information about a route similar to the initial route by using the user's location information (for example, a latitude value and a length value), and location measurement time information. The information used by the computing device 100 in detecting information about the user's route may be, as described above, information about a user mode and / or information about content generated by a user, included in the information about a route initial.

The computing device 100 can detect information indicating the user's intended route using a machine learning algorithm. That is, the computing device 100 can analyze information about an initial route based on a profile or model of a user's location generated based on information from the user's location history. The analysis procedure can be performed using a decision tree learning procedure based on the profile or model of a user's location or an artificial neural network, but the analysis procedure is not limited to this. The computing device 100 can detect information about a user's route, including a route similar to an initial route based on the result of the analysis of information about an initial route.

A user's location profile or model, generated by machine learning, can be expressed as cumulative route information (or a cumulative route profile or model) or past route information (or a past route profile or model). The computing device 100 can detect a user's route information, including a route similar to an initial route based on cumulative route information or past route information.

When information about the user's route, including a route similar to an initial route, is detected using the statistical analysis procedure or the machine learning procedure (or a machine learning algorithm) described above, the computing device 100 can detect, from the information detected about the user's route, information about the rest of the route that indicates the user's planned route.

If the computing device 100 detects a plurality of pieces of information about the user's path, the computing device 100 can select information about the most frequently used path of the user from the plurality of pieces of information detected about the user's path. user, such as information about the user's path.

The plurality of pieces of information about the user's route can include information about a route that is the same as the initial route and different from the rest of the routes. For example, if the information about an initial route is "point A ^ point B (or from point A to point B)", the plurality of pieces of information about the user's route may include information about a user's first route that is "point A ^ point B ^ point C", information about a user's second route that is "point A ^ point B ^ point D ^ point E", and information about a user's third route that is "point A ^ point B ^ point F ^ point E ".

If the number of times the information on the second user route is used is the largest of the information on the first to the third user route, the computing device 100 may select the information on the second user route as the information on the user's path relative to an initial path. When information about the user's second route is selected, computing device 100 can detect "point B A point F to point E" as information about a user's intended route.

When the information about the user's expected route is detected, the computing device 100 provides the user with the user's expected route, in step S205. The computing device 100 may provide the user's intended route extending from an initial route, as shown on screen 120 in FIG. 1.

By detecting the information indicating the user's intended route through an external device, the procedures performed by the computing device 100 described above can be used.

Fig. 3 is an operational flow chart of a procedure for providing personalized information according to another exemplary embodiment. In the procedure of Fig. 3, a function of tracking a user's route to a destination point is added to an exemplary embodiment of Fig. 2.

Steps S301 to S305 of Fig. 3 are respectively similar to steps S201 to S205 of Fig. 2, and therefore their description will be omitted below.

In step S306, computing device 100 tracks a user's location from a current point 102 to a destination point 105. Destination point 105 is based on the user's predicted route 104. By tracking the location of a user, computing device 100 can variably control a range of measurement of a user's location based on at least one of the user's speed of movement, information from the user's surrounding environment and / or the user's intended route 104. In particular, the computing device 100 can determine a next location measurement time (or a next location measurement point) based on the user's planned route 104. By following the location tracking of the user described above, the battery consumption of the computing device 100 can be reduced.

At step S307, computing device 100 can update the user's location history information based on information about the location of the tracked user.

Fig. 4 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Based on the procedure in Fig. 4, personalized information can be provided according to the number of uses (or a usage count) of a user's intended route.

Steps S401 to S404 in Fig. 4 are respectively similar to steps S201 to S204 in Fig. 2, and therefore their description will be omitted below.

When information indicating the user's intended route 104 is provided in step S405, the computing device 100 may provide information of different interest depending on the usage count of the user's intended route 104. The information indicating the user's intended route 104 may include information regarding the usage count of the user's intended route 104. Information of different interest may include, but is not limited to, a topic article. For example, computing device 100 may provide different user activities (or user mode) according to the usage count of the user's intended route 104.

Fig. 5 illustrates an example of a screen for providing information of different interest based on the usage count included in the information indicating the user's intended route 104. A screen 510 of FIG. 5 shows an example in a case where the usage count of the predicted route 104 is n. A screen 520 in FIG. 2 illustrates an example in a case where the usage count of the predicted route 104 is m, where n and m are natural numbers equal to or greater than 1. For example, n can be 2 and m can be be 10.

Screen 510 of Fig. 5 provides points of interest A1, A2 and A3. Screen 520 in Fig. 5 provides points of interest B1, B2, B3 and B4. Points of Interest A1, A2, and A3 can be information based on different types of content (for example, a restaurant, a gas station, or a shopping mall), different topic items, or different user activities. Points of Interest B1, B2, B3, and B4 can be information based on different types of content, different topic articles, or different user activities.

The computing device 100 can change information about the points of interest A1, A2, A3, B1, B2, B3 and B4 according to a user input. A user input can include, for example, unlimited information about a desired point of interest. For example, a user entry may include a request to change a point of interest.

The computing device 100 can provide information of interest as shown on the screen 510 and the screen 520 based on the usage count and information about a user included in the information indicating the user's planned route 104.

Fig. 6 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. The procedure of Fig. 6 is an example of providing personalized information depending on whether the predicted route 104 based on an initial route is detected from the user's location history information.

Steps S601 to S604 of Fig. 6 are respectively similar to steps S201 to S204 of Fig. 2, and therefore their description will be omitted below.

At step S605, computing device 100 determines whether information indicating intended route 104 based on initial route 103 is detected from the user's location history information. As a result of the determination, if the information indicating the expected route 104 is detected from the user's location history information, the computing device 100 provides information indicating the expected route 104 in step S606, as in step S205.

If the information indicating the intended route is not detected from the user's location history information in step S605, computing device 100 tracks a user's location in step S607. The computing device 100 can track the location of a user as in step S202 described above. If the information indicating the intended route 104 is not detected from the user's location history information, the initial route 103 may be an unusual route for the user. The unusual route may be based on unusual events (eg travel, new destination, party).

In step S608, computing device 100 can provide the location information of the tracked user and update the location information of the user location based on the location information of the tracked user.

Fig. 7 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 7 illustrates an example where there is a region where the movement of people is active at the present time based on the planned route 104. FIG. 7 is an operational flow chart based on computing device 100 and server 700.

Steps S701 to S705 of Fig. 7 are respectively similar to steps S201 to S205 of Fig. 2, and therefore their description will be omitted below.

In operation S706, server 700 collects information about a region in which the movement of people is currently active (or a region with a large floating population). Server 700 may include, but is not limited to, an external device such as a location information collection server or a custom information delivery server.

Server 700 may collect information about, but is not limited to, a region in which people movement is currently active based on a predetermined number of people. For example, the server may collect information from the top ten regions with active movement of people at a current time for each administrative region (for example, Maetandong of Suwon City). Information about the region can be expressed as location information (or coordinate information). The preset number of people and the top ten for each administrative region described above can be included in a first parameter that is used to collect information about the region in which the movement of people is currently active. The information included in the first parameter is not limited to them.

In step S707, computing device 100 requests information from server 700 about a region in which the movement of people is currently active. In step S708, server 700 transmits the collected information about a region in which the movement of people is currently active, to the computing device 100.

In step S709, the computing device 100 receives the information about a region in which the movement of people is active at a current time. In operation S710, computing device 100 detects information about a region adjacent to planned route 104 from information about a region in which the movement of people is currently active, by using a second parameter.

Fig. 8 illustrates an example of providing information about regions C1, C2 and C3 adjacent to planned route 104. In operation S710, to detect the adjacent regions C1, C2, and C3 as shown in FIG. 8, the computing device 100 can use the second parameter that includes distance information and numerical information. The information included in the second parameter is not limited thereto.

Distance information may include, for example, information such as 100m or 200m. If the distance information is 100 m, the computing device 100 can detect information about a region within 100 m from the planned route 104. The number information can refer to various regions and can include integers such as 2, 3, or 4. If the number information is 3, the computing device 100 can detect information about three regions adjacent to the intended route 104.

When the 100m distance information and the 3 numerical information are used, the computing device 100 can detect information about three regions within 100m from the predicted route 104. The information included in the first and second parameters can be set in advance. The information included in the second parameter can be entered by a user. The information included in the second parameter can be selectively used by a user.

In operation S711, the computing device 100 provides the detected regional information as shown in Fig. 8. In Fig. 8, the number information included in the second parameter is 3. If the number information included in the second parameter is 2, computing device 100 can provide information about adjacent regions C1 and C2. If the number information included in the second parameter is 1, the computing device 100 can provide information about the adjacent region C3.

The sizes of the adjacent regions C1, C2 and C3 can be determined based on the number of people. With reference to Fig. 8, a quantity of people movement is large in an order of C3, C1 and C2. The adjacent regions C1, C2 and C3 are expressed as circles, but without limitation. For example, the adjacent regions C1, C2 and C3 can be expressed as squares or triangles. The distance information included in the second parameter may be a distance between, but not limited to, a central point of the adjacent regions C1, C2 and C3 and a boundary line of the intended route 104. The planned route 104 boundary line denotes a planned route 104 boundary line adjacent to the adjacent regions C1, C2 and c 3. For example, in a case of adjacent region C1, the planned route 104 boundary line It is the limit line on the right side of planned Route 104.

Fig. 9 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 9 shows another example of providing information about a region in which the movement of people is active at the present time based on the planned route 104. FIG. 9 is an operational flow chart based on computing device 100 and server 700.

Steps S901 to S906 of Fig. 9 are respectively similar to steps S701 to S706 of Fig. 7, and therefore their description will be omitted below.

In step S907, computing device 100 requests regional information from server 700. By requesting regional information, computing device 100 can transmit information indicating the expected route 104 detected in step s 904 to server 700. In step S907, computing device 100 may further transmit the second parameter to server 700. The second parameter may include a current time.

In step S908, server 700 can detect information about a region adjacent to planned route 104 from information about a region in which the movement of people is currently active, collected in step S906, using at least one of the received information indicating the planned route 104 and the second parameter. Server 700 can set the second parameter in advance, and can use the second parameter when detecting information about adjacent regions using the received information indicating the intended route 104.

In step S909, server 700 transmits information about regions C1, C2, and C3 adjacent to intended route 104 to computing device 100. In step S910, the computing device 100 provides the received information about the adjacent regions C1, C2 and C3 as illustrated in Fig. 8.

Fig. 10 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 10 shows an example of providing information about a region in which the movement of people is active at a current moment and information about a point of interest at a current moment based on planned route 104. FIG. 10 is an operational flow chart based on computing device 100 and server 700.

Steps S1001 to S1006 of Fig. 10 are respectively similar to steps S901 to S906 of Fig. 9, and therefore their description will be omitted below.

In step S1007, server 700 detects information about a point of interest included in a region where the movement of people is currently active. Point of interest information can be determined based on information about a user.

In step S1008, computing device 100 requests regional information and information about the point of interest from server 700. In step S1009, server 700 transmits to regional computing device 100 the regional information collected in step S1006 and information about the point of interest included in each region, detected in operation S1007.

In step S1010, computing device 100 detects information about a region adjacent to planned route 104 from the received regional information. In step S1011, computing device 100 provides the detected adjacent regional information and information about the point of interest included in the detected adjacent region.

Fig. 11 illustrates an example of providing the adjacent regional information and information about a point of interest included in the adjacent regional information provided by a computing device in step S1011. Referring to FIG. 11, computing device 100 provides information about regions C1, C2, and C3 adjacent to planned route 104 and points of interest C1-1, C1-2, C1-3, C1-4, C2 -1, C3-1, C3-2, C3-3 and C3-4 included in the adjacent regions C1, C2 and C3. The adjacent regions C1, C2 and C3 are regions in which the movement of people is active at the present time.

With reference to Fig. 11, the number of points of interest included in the adjacent regions C1, C2 and C3 may be different according to the adjacent regions C1, C2 and C3. Referring to Fig. 11, computing device 100 provides information on the greatest number of points of interest C3-1, C3-2, C3-3, and C3-4, in region C3. While the number of points of interest may be different depending on the sizes of the adjacent regions C1, C2, and C3, the number of points of interest can also be provided regardless of the sizes of the adjacent regions C1, C2, and C3. For example, fewer points of interest can be included in the adjacent region C3 than in the adjacent regions C1 and C2.

The computing device 100 can change information about points of interest included in the adjacent regions C1, C2 and C3 based on the established information about points of interest. The computing device 100 can set or change information about points of interest included in the adjacent regions C1, C2 and C3 based on information about a user or according to a user input.

Although the computing device 100 provides information about a point of interest based on information about a user, the information about a point of interest provided by the computing device 100 is not limited thereto.

For example, in step S1008, computing device 100 may request server 700 for information about a point of interest from another user. The other user may be a user who allowed information about a point of interest to be provided to the user of the computing device 100. In step S1008, when information about a point of interest is requested from another user, computing device 100 may transmit identifying information (eg, a name or phone number) from another user to server 700.

To provide information about a point of interest from another user, server 700 can detect not only information about a point of interest based on information about the user of computing device 100 but also information about a point of interest based on information about another user in step S1007.

In step S1009, server 700 transmits information about another user's point of interest to computing device 100. In step S1011, computing device 100 may provide information about the point of interest of the other user included in a detected adjacent region.

When there are several more users, the computing device 100 may further provide user identification information corresponding to point of interest information to intuitively identify point of interest information for each user in step S1011. An intuitive identification procedure for information about a point of interest of each user is not limited to them. For example, the computing device 100 may provide information about a point of interest for each user in different colors or shapes, and provide guiding information (eg, a legend) about the colors or shapes corresponding to the respective users.

Fig. 12 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 12 shows an example of changing information about a point of interest included in a region adjacent to planned route 104. FIG. 12 is an operational flow diagram based on computing device 100 and server 700.

Steps S1201 to S1211 of Fig. 12 are respectively similar to steps S1001 to S1011 of Fig. 10, and therefore their description will be omitted below.

When the personalized information as illustrated in Fig. 11 is provided in step S1211, and when a request to change a point of interest is received in step S1212, the computing device 100 can change information about points of interest C1-1 , C1-2, C1-3, C1-4, C2-1, C3-1, C3-2, C3-3 and C3-4 included in the adjacent regions C1, C2 and C3 for information on points of interest C1- 4, C1-5, C1-6, C2-2, C2-3, and C3-5, as illustrated in Fig. 13 in step S1213. FIG. 13 illustrates an example of providing information about adjacent regions and information about a point of interest included in the adjacent region, provided by computing device 100.

The request to change a point of interest may be received based on, for example, a point of interest change article 1101 or a point of interest information adjustment article 1102 illustrated in Figs. 11 and 13, but not limited thereto.

Item 1101 POI Change is an item used to change a POI type. A type of point of interest can be classified as, for example, a park, a restaurant (Korean, Chinese, Japanese, etc.), a shopping mall or an exhibition hall, etc. At least one type of point of interest that is registered in the article 1101 of change of point of interest can be automatically established based on the information about a point of interest included in the information about a user or can be established by a user.

At least a piece of information about a point of interest can be registered in the article 1101 of change of point of interest. For example, if four pieces of information about a point of interest are recorded in the POI article 1101, each time the POI article 1101 is toggled, the computing device 100 may toggle sequentially through of four types of points of interest through the adjacent regions C1, C2 and C3.

For example, if the information on points of interest C1-1, C1-2, C1-3, C1-4, C2-1, C3-1, C3-2, C3-3 and C3-4 included in the regions adjacent C1, C2 and C3 in Fig. 11 is information about a first type point of interest (eg Korean restaurant), and item 1101 toggles point of interest toggles, computing device 100 can change information on the POI of the first type (eg Korean restaurant) included in the adjacent regions C1, C2 and C3 for information on a POI of a second type (eg shopping center). Accordingly, computing device 100 can provide information on points of interest C1-4, C1-5, C1-6, C2-2, C2-3 and c 3-5 as illustrated in Fig. 13 through the adjacent regions C1, C2 and C3.

If the information about a point of interest of the second type is provided (for example, a shopping center) and the change of point of interest article 1101 is alternated, the computing device 100 can change the information about the point of interest of the second type (eg shopping mall) included in adjacent regions C1, C2 and C3 for information on a third type POI (eg Chinese restaurant).

If the information about a point of interest of the third type is provided (for example, a Chinese restaurant), and the change of point of interest article 1101 is alternated, the computing device 100 can change the information about the point of interest of the third type (for example, Chinese restaurant) included in the adjacent regions C1, C2 and C3 to obtain information about a point of interest of a fourth type (for example, bakery).

If the information about a point of interest of the fourth type (for example, bakery), and the article 1101 of change of point of interest is alternated, the computer device 100 can change the information about the point of interest of the fourth type (for example , bakery) included in the adjacent regions C1, C2 and C3 for information on a point of interest of the first type (eg Korean restaurant).

If information on points of interest included in the adjacent regions C1, C2 and C3 is provided as illustrated in Fig. 11, the computing device 100 can change the information on points of interest included in the adjacent regions C1, C2 and C3 according to a user input using POI information adjustment article 1102.

A user input received using the POI setting article 1102 may include at least one of a touch input, a user voice input, a proximity touch input, and an input based on user gestures. A user input received using the POI information adjustment article 1102 can be expressed as a selection or control of the POI information adjustment article 1102.

When the point of interest information setting article 1102 is controlled, the computing device 100 can provide a screen as illustrated in Fig. 14. Fig. 14 illustrates an example of a screen including a list 1410 of points of interest. search interest. The information about points of interest included in the search points of interest list 1410 (hereinafter referred to as list 1410) illustrated in Fig. 14 may be similar to the information included in a topic article.

When a user input that selects a 1411 Landscape item, a 1412 Cultural item, and a 1413 Relationships item is received based on list 1410, and a 1420 Complete button is selected, the computing device 100 can provide information about points of interest (the Article 1411 Landscape, Article 1412 Cultural and Article 1413 Relations) selected from the adjacent regions C1, C2 and C3. Article 1413 Relations indicates points (or places) where people meet frequently.

In Fig. 14, when a user input that selects item 1411 Landscape, item 1412 Cultural, and item 1413 Relations is received according to list 1410, and a button 1430 Reset is selected, the computing device 100 can reset information about selected points of interest. As the information about the selected points of interest is restored, the computing device 100 can provide a screen in which a selected state of the article 1411 Landscape, the article 1412 Cultural and the article 1413 Relations illustrated in Fig. 14 is canceled.

Referring to Fig. 12, information on points of interest of all kinds that may be included in a collected region is received in step S1209, and computing device 100 provides information on some points of interest (eg, Korean restaurant) included in adjacent regions C1, C2, and C3 in step 51211. Thus, in accordance with a request to change a point of interest, received in step 51212, computing device 100 can provide information about other points of interest ( for example, Chinese restaurant), which are not provided in step S1211, in step S1213.

When all the information on points of interest received in step S1209 of Fig. 12 is provided, and when the request to change a point of interest is received in step S1212, computing device 100 can transmit a request to change a point of interest included in a detected region, to server 700. Server 700 can provide computing device 100 with information about a point of interest provided in step S1209 (eg, Korean or Chinese restaurant) and information about other points of interest (p (eg, shopping center) enter information about points of interest included in the detected region.

Server 700 can determine information about, but is not limited to, other points of interest based on information about a user. For example, server 700 may receive information about other points of interest (eg, mall) from computing device 100 upon receipt of a request to change a point of interest from computing device 100.

Upon receiving information indicating other points of interest from the computing device 100, the server 700 can detect information related to other points of interest from the points of interest detected in the operation S1207, but is not limited thereto. For example, upon receiving information about other points of interest from the computing device 100, the server 700 may perform operation S1207 again to detect information about other points of interest included in the collected region. When information about other points of interest is detected, the server 700 transmits the detected information about the other points of interest to the computing device 100.

Fig. 15 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 15 shows an example of providing information about a point of interest based on a point (or a specially designated point) on planned route 104.

Steps S1501 to S1505 of Fig. 15 are respectively similar to steps S201 to S205 of Fig. 2, and therefore their description will be omitted below.

In step S1506, server 700 collects information about points of interest from a user in each region based on information about a user.

In step S1505, when screen 120 of FIG. 1 is provided by computing device 100, and a request for information about a point-of-interest point based on step S1507 is received, the device The computer scientist requests the point-based point of interest information to the server 700 in step S1508. Point-based point of interest information may include, but is not limited to, information about a point of interest located less than 100 m from the point. 100m can be included in the condition (or parameter) information used to provide information about a point of interest based on the point. The condition information can be preset or configured by the user.

The point includes at least one point on planned route 104. The point may include, for example, current point 102 and destination point 105 on planned route 104, but is not limited thereto.

Requesting information about a point of interest based on a predetermined point can be entered as, but not limited to, touch user input. For example, the point-of-interest POI request may include a user voice input (eg, point A) indicating the point. A user input or a user voice input requesting information about a point-of-interest point can include an input that designates a particular point on intended route 104.

For example, when the screen 120 of Fig. 1 is provided by the computing device 100 in step S1505, when a user input indicating a request for information about a point of interest based on the current point 102 is received at the In step S1507, the computing device 100 transmits the information request about the point of interest to the server 700 in step S1508.

In step S1509, server 700 detects information about a point of interest based on the point between the point of interest information collected in step S1506. In step S1510, the computing device 100 transmits the detected information about the point of interest based on the point, to the computing device 100.

In step S1511, the computing device 100 provides the information about the point of interest based on the point. When the point is current point 102, computing device 100 can provide a screen illustrated in FIG. 16a at step S1511. Fig. 16a illustrates an example of a screen providing information about a point of interest based on current point 102 on planned route 104.

When the screen 120 of FIG. 1 is provided by the computing device 100 in step S1505, and the requested point in step S1507 is the destination point 105, the computing device 100 can provide a screen illustrated in FIG. 16b in operation S1511. Fig. 16b illustrates an example of a screen providing information about a point of interest based on destination point 105 on planned route 104.

When the screen 120 of Fig. 1 is provided by the computing device 100 in step S1505, and the requested point in step S1507 is the current point 102 and the destination point 105, the computing device 100 can provide an illustrated screen in Fig. 16c in step S1511. Fig. 16c illustrates an example of a screen providing information about a point of interest based on current point 102 and destination point 105 on planned route 104.

Fig. 17 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 17 illustrates an example of changing information about a point of interest based on a point (or a specially designated point) on planned route 104.

Steps S1701 to S1711 of Fig. 7 are respectively similar to steps S1501 to S1511 of Fig. 15, and therefore their description will be omitted below.

In step S1711 of Fig. 17, when one of the screens in Figs. 16a to 16c is provided by computing device 100, and a request for information change about a point of interest is received in step S1712, computing device 100 changes the information about point of interest based on the point in step S1713 .

For example, when information about a point of interest is provided as illustrated in Fig. 16a in step S1711, and the item 1101 change of point of interest alternates in step S1712, the computing device 100 can change the information about the point of interest (eg, an exhibition hall) provided based on the current point 102 illustrated in Fig. 16a to information about another point of interest (eg, a shopping mall) in step S1713.

When information about a point of interest is provided as illustrated in Fig. 16b in step S1711, and the change of point of interest item 1101 alternates in step S1712, the computing device 100 can change the information about the point of interest (eg Korean restaurant) provided based on destination point 105 illustrated in Fig. 16b to information on another point of interest (eg Chinese restaurant) in step S1713.

When information about a point of interest is provided as illustrated in Fig. 16c in step S1711, and item 1101 change of point of alternate in step S1712, computing device 100 can change the information about the point of interest (for example, a service station) provided according to the current point 102 and destination point 105 illustrated in Fig. 16c to information about another point of interest (eg, a vehicle maintenance shop) in step S1713.

Referring to Fig. 17, not all of the information received in step S1710 about point-based points of interest is provided by computing device 100 in step S1711. The computing device 100 can provide information about a point of interest according to the priority of the information received about the points of interest depending on the point. The priority can be determined based on, but is not limited to, the number of points of interest based on the point. The priority can be determined based on information about a user.

When a request to change a point of interest is received in step S1712, the computing device 100 can change the information from point-of-interest information based on the point to information about another point of interest, according to the priority of the information on points of interest received in operation S1710.

If the computing device 100 has provided all the information about the points of interest based on the point received in step S1710, in step S1711, then steps S1712 and S1713 of Fig. 17 can be modified so that the information about the points of interest depending on the point is changed depending on the communication between the computing device 100 and the server 700.

For example, when the request for change of information about a point of interest is received in step S1712, computing device 100 transmits the request for change of information about a point of interest based on the point to server 700. Server 700 detects information about another point of interest that is different from the information about a point of interest depending on the point, from the information about points of interest collected in operation S1706. Server 700 transmits the detected information about another point of interest to computing device 100. The computing device 100 can change the information about the point of interest based on the point to the information received about another point of interest.

When the request to change the point of interest is transmitted from the computing device 100 to the server 700, the computing device 100 can transmit information related to another point of interest (point of interest type information) to the server 700 but is not limited to the same. For example, server 700 determines a priority over a point of interest type over a user, based on information about a user. The server 700 can detect information about a point of interest based on the point of the information about points of interest collected in the operation S1706, according to the determined priority and transmit it to the computing device 100.

While Figs. 7, 9, 10, 12, 15, and 17 illustrate operational flowcharts based on communication between computing device 100 and server 700, the procedures may also be performed only by computing device 100, without the involvement of server based 700 in a function of the computing device 100.

Information on a point of interest described with reference to Figs. 10-17 can be detected by further considering the site profile information. Information on a point of interest described with reference to Figs. 10-17 can include information that recommends content based on place profile information and information about a user, such as detailed information. For example, when information about a point of interest is selected based on user input, information that is recommended by the content provided at the selected point of interest may be provided through an additional window (for example, a popup) , but is not limited to them. For example, content recommendation information may be provided as at least one of a map form and a notification form. The content may refer to the content described with reference to exemplary embodiments of topic articles to be described later.

Fig. 18 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Referring to Fig. 18, after providing the planned route 104, the information about a point of interest is provided according to a received notification message.

Steps S1801 to S1805 of Fig. 18 are respectively similar to steps S201 to S205 of Fig. 2, and therefore their description will be omitted below.

In step S1805 of FIG. 18, when information indicating the intended route 104 is provided as shown on screen 120 of FIG. 1, and a context is produced for transmitting a notification message in a car 1800 in the In step S1806, car 1800 transmits a notification message to computing device 100 in step S1807. Car 1800 is a device connected to computing device 100.

The context for transmitting a notification message may include, but is not limited to, a battery replacement or refueling context. The contexts described above can be detected using a sensor or the like included in the 1800 car.

When a notification message is received, the computing device 100 provides information about a point of interest adjacent to the intended route 104, between the points of interest related to the notification message, in step S1808.

For example, if a notification message notifies the replacement of the 1800 car battery, the computing device 100 may provide information about a vehicle battery replacement center (or car maintenance shop) located near Route 104 provided in step S1808. If a notification message notifies the refueling of the 1800 car, the computing device 100 can provide information about a refueling center located near route 104 provided in step S1808.

Fig. 19 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 19 illustrates an example of providing information about another user's route and another user's activity. The other user refers to a person who allowed the user of computing device 100 to access information about a route of the other user. The other person may be at least one person from the user's children, the user's parents, etc. who will be notified of the user's path.

In step S1901, another computing device 1900 transmits a route tracking permission signal to computing device 100. In step S1902, the other computing device 1900 tracks the location of a user of the other computing device 1900 and detects the activity of the user of the other computing device 1900. The other computing device 1900 may be a device such as the computing device 100 described with reference to FIG. 1. Tracking the location of the user can be performed as described with reference to step S202 of FIG. 2 and as described with reference to Fig. 1. Tracking the user's location can be done using a sensor, a GPS receiver, a network location information receiver included in the other 1900 computing device, or an IoT sensor that is not included but not limited to the other 1900 computing device.

In step S1903, the other computing device 1900 transmits the detected user location information and detected information about the user's activity to the computing device 100.

In step S1904, computing device 100 obtains information about a user's initial route from other computing device 1900 based on the received user location information and received user activity information. The information about the initial route can be obtained in the same way as in operations S202 and S203 in Fig. 2.

In step S1905, the computing device 100 detects information about a predicted route of the user of the other computing device 1900 from the user location history information of the user of the other computing device 1900 based on the information obtained about the initial route. The user location history information of the user of the other computing device 1900 may be stored in the computing device 100 or in an external device such as a home sync, synchronized with the computing device 100, or in the other computing device 1900.

The computing device 100 may establish a connection to another device in step S1905 according to a location where the location information of the user location of the other computing device 1900 is stored. For example, if the user location history information from the other computing device 1900 is stored on a home sync, the computing device 100 may establish a connection to the home sync while connected to the other computing device 1900. When connected to home sync, computing device 100 can read the user's location history information from home sync or request information indicating the user's expected path from home sync.

In step S1906, computing device 100 provides information indicating the expected path of the user of the other computing device 1900 and information on the user activity of the user of the other computing device 1900 together. Information on user activity may be information about the user modes described above, and may be displayed on the intended route. In this way, the user of the computing device 100 may know a location of the user of the other computing device 1900 and the user activity information of the user of the other computing device 1900 at each location.

Fig. 20 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. FIG. 20 is an example of providing routes of the user of computing device 100 and the user of another computing device 2000 together.

The user of the other computing device 2000 refers to a person who allowed the user of the computing device 100 to access information about a path of the user of the other computing device 2000. The other computing device 2000 may be the same device but not limited to the other computing device 1900 illustrated in FIG. 19.

In step S2001 and S2002, the other computing device 2000 obtains information about an initial route from the user of the other device 2000 in the same manner as step S202 and S203. Step S2001 may include a function to determine if the user's location is moved, performed in step S201 of Fig. 2.

In operations S2003 and S2004, computing device 100 obtains information about an initial route from the user of computing device 100 in the same manner as step S202 and S203 in Fig. 2. Steps S2003 may include a function to determine whether the user's location is moved, performed in step S201 in Fig. 2.

In step S2005, computing device 100 transmits to the other computing device 2000 a signal requesting to provide a route to the user of the other computing device 2000. When the user of the other computing device 2000 accepts the request to test a route, the other computing device 2000 transmits the user's route information obtained so far to the computing device 100 in step S2006. In step S2006, the other computing device 2000 may transmit a message notifying that access to route information is allowed.

In step S2007, computing device 100 provides information about the user's initial path of the other device 2000 and information about the user's initial path of computing device 100. Fig. 21 illustrates examples of a display that can be provided in accordance with the flow chart of Fig. 20. In step S2007, computing device 100 can provide a display 2110 of Fig. 21.

Referring to the screen 2110 of Fig. 21, a start point 2111, a current point 2112, and a user initial route 2113 of the other computing device 2000, and the start point 101, the current point 102 and the route User initial 103 of computing device 100 are provided together.

In step S2008, computing device 100 detects information indicating the intended path of the user of computing device 100. Step S2008 can be performed similarly to step S204 in Fig. 2.

In step S2009, the other computing device 2000 detects information indicating the intended path of the user of the other computing device 2000. Step S2009 can be performed similarly to step S204.

In step S2010, the other computing device 2000 transmits information indicating the intended route detected in step S2009 to the computing device 100. Accordingly, in operation 2011, computing device 100 may provide a screen 2120 of FIG. 21.

Referring to screen 2120 of FIG. 21, computing device 100 provides information about a starting point 101, a current point 102, a starting route 103, a planned route 104, and a destination point 105 of the user of device 100 computer, a current point 2112, an initial route 2113, a predicted route 2121 of the user of the other computing device 20, and the destination point 105 which is the same as that of the user of the computing device 100.

In step S2012, computing device 100 tracks a user location of computing device 100. In step S2013, the other computing device 2000 tracks a user location of the other computing device 2000, and transmits user location tracking information to the computing device 100 in step S2014.

In step S2015, the computing device 100 provides the location information of the user of the computing device 100 tracked by the computing device 100 and the information on the location of the user of the other computing device 2000 tracked by the other computing device 2000. The information about the planned routes 104 and 2121 and information about the current points 102 and 2112 provided through the screen 2120 of Fig. 21 can be changed according to the location information of the previous user.

According to the operational flow diagram illustrated in Fig. 20, the user of the computing device 100 can verify a state of movement of the user of the other computing device 2000 that is directed towards the destination point 105 which is the same as that of the user of computing device 100.

While the information about a user route of the computing device 100 and the information about a user route of the other computing device 2000 can be provided in different colors, a method for distinguishing the routes of the two users is not limited to them. For example, an image or text can be displayed that tells users at current 101 and 2112. An image that indicates a user can be a face image or an Avatar that represents the user, but is not limited to them. Text indicating a user may include, but is not limited to, user identification information (eg, user name).

In FIG. 20, the other computing device 2000 may transmit route information from one user to the computing device 100 each time a location of the user of the other computing device 2000 is determined. In this way, the computing device 100 can provide information about the mobile states of the user of the computing device 100 and the user of the other computing device 2000 in real time.

The operational flow diagram illustrated in Fig. 20 can be changed so that the user paths of the computing device 100 and the user of the other computing device 2000 are provided in real time.

Referring to Fig. 20, before tracking the location of the user of computing device 100, computing device 100 may transmit a signal requesting to provide a route to the other computing device 2000. When a signal is received that agrees to provide a route from the other computing device 2000, the computing device 100 can provide location information of the user information of the other computing device 2000 provided from the other computing device 2000 and the location information of the device user 100 computer scientists together in real time.

Although the operational flowchart illustrated in Fig. 20 is an example of providing a user path of computing device 100 and a user path of other computing device 2000 together, the operational flowchart can be changed so that they are provided together a user path of computing device 100 and paths of a plurality of other users.

The procedure illustrated in Fig. 20 can be changed so that information about a plurality of devices is provided which allowed the user of computing device 100 to access the route information thereof, and a route of at least one device selected from the plurality of devices. When the screen 110 of FIG. 1 is provided to select at least one of the plurality of devices, the computing device 100 can provide information on a plurality of selectable devices. The plurality of devices may include previously registered person devices on computing device 100. Persons who are previously registered in computing device 100 may include persons registered in a phone book or registered as friends of the user of computing device 100 according to an exemplary embodiment, but without limitation.

The recommendation topic articles described with reference to Figs. 22 to 34 below may be included in information on points of interest described with reference to Figs. 4, 10, 12, 15, 17, and 18. Thus, Figs. 23, 27, 29 and 31 to 34 can be included in the information detection operation on a point of interest carried out in Figs. 4, 10, 12, 15, 17 and 18, but is not limited thereto.

Fig. 22 is an example of providing a geographic location based recommendation topic article as personalized information.

Referring to Fig. 22, if content related to a point 2202 marked on a map 2201 can be generated, computing device 100 may provide recommendation topic articles TH1 through TH9.

A context in which content related to a point 2202 marked on a map 2201 can be generated may include a context in which the user of computing device 100 is near or at point 2202, but exemplary embodiments are not limited thereto. For example, the above context may include a context in which a user input is received that points to point 2202 on map 2201. A nearby position may be within 50m of point 2202, but is not limited thereto. .

Recommendation topic articles TH1 through TH9 can include topic articles that are filtered from a plurality of topic articles according to context. For example, if point 2202 is store A at Gangnam station, recommendation topic items TH1 to TH9 may include topic items (eg coffee, dating, study and / or meeting) that are filtered from a plurality of theme articles (coffee, bicycle, meeting, dating, movie, driving, exercise, shopping, ..., (omitted), ..., studying, beauty care, staying and / or hiking, etc.) .

Referring to Fig. 22, a display 2203, in which recommendation topic articles TH1 to TH9 are provided, may include a display title 2204 (eg, "GENERATE NEW CONTENT"), a cancel article 2205 to cancel the generation of new content, a region 2206 that shows recommendation topic articles TH1 to TH9, and a full recommendation topic article selection article 2207 "Done", but is not limited to them.

When a user input that selects cancellation article 2205 is selected to generate new content, computing device 100 can change screen 2203 to a previous screen or a home screen or an application screen.

After receiving a user input selecting one of the recommendation topic articles TH1 through TH9, and receiving a user input selecting the entire recommendation topic article selection article (for example, Done button) 2207, computing device 100 can provide a screen on which new content can be generated. The screen for generating new content can be provided as illustrated in Fig. 26 to be described later.

User input selecting cancel article 2205 to cancel new content generation, user input selecting recommendation topic article TH1, and user input selecting full article selection item 2207 The recommendation can be made by, but is not limited to, at least one of a touch input, an input based on user gestures and an input based on user voice signal.

Fig. 23 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 23 illustrates an example where a recommendation topic article is provided as personalized information, according to a user's request that the content of a selected topic article is generated and logged on the computing device 100.

Referring to Fig. 23, when the user of computing device 100 in step S2301 receives a request to generate content, computing device 100 obtains context information in step S2302.

A request to generate content may be made by, but is not limited to at least one of a touch input, an input based on the user's gesture, and an input based on the user's voice signal.

For example, a request to generate content can be received through an existence detection screen, such as a touch screen. In other words, the computing device 100 may receive a request to generate content by touching or pointing to at least one location on a touch screen with a user's finger or using a stylus. The location on the touch screen that is touched or pointed to can be a location where an item is marked to request the generation of content or information by which it is recognized that touching or pointing indicates a request to generate content.

Fig. 24 illustrates an example of a screen illustrating a request to generate content according to an exemplary embodiment. As illustrated in FIG. 24, when the user touches a point A 2401 on a map 2400 provided using computing device 100 as illustrated in FIG. 24, computing device 100 may determine that a request is received to generate content in point A 2401. A user touch may include, but is not limited to, a long touch. A touch by a user can be preset to indicate a request to generate content.

In step S2302, computing device 100 obtains at least one of user-based context information from user of computing device 100 and geographic location-based context information. User-based context information and geographic location-based context information are as previously described in the present disclosure.

The user-based context information can be obtained using sensors included in the computing device 100, a GPS receiver, a network location receiver, user history information from the computing device 100, and / or information about a user. The information used to obtain context information based on the user is not limited to the above. The geographic location based context information can be received and obtained from an external device of the computing device 100. The external device, for example, may include a location profile information delivery server or a computing device located at a corresponding location.

Operation S2302 can be divided into a user-based context information retrieval operation and a geographic location-based context information retrieval operation. Obtaining user-based context information and obtaining geographic location-based context information can be performed simultaneously or sequentially. When operations are performed sequentially, the order can be established in advance. The default order can be changed by a user.

When the context information is obtained, the computing device 100 detects a recommendation topic article based on the context information obtained in step S2303.

For example, the context information obtained in step S2302 includes information indicating that the user of computing device 100 is in store A at the Gangnam station, and content topic articles that are primarily generated by the user of the device. 100 computer at store A in Gangnam station are appointments and meetings, and a theme item that is mainly generated in store A at Gangnam station is appointments, the device 100 computer can detect appointments as a topic article from recommendation in operation S2303. Mainly generated content can indicate content with high frequency generation. The mainly generated topic article can indicate a topic article with high frequency generation.

In the example above, information stating that the user is in store A at Gangnam station and information about a topic item mainly generated by user in store A at Gangnam station can be included in the information of user-based context of computing device 100. Information on a theme item that is primarily user-generated in Store A at Gangnam Station can be included in context information based on geographic location.

For example, the context information obtained in step S2302 includes information indicating that the user of computing device 100 is close to store A at Gangnam station, and content topic articles that are primarily generated by the user of the computing device 100 in store A at Gangnam station are appointments and meetings, computing device 100 can detect appointments and meetings as a recommendation topic item in operation S2303.

For example, the context information obtained in operation S2302 includes information indicating that the content theme articles that are mainly generated in store A at Gangnam station are coffee, Dating and meetings and the preferred content theme articles by the user of the computing device 100 are coffee, food, shopping and games, the computing device 100 can detect coffee as a recommendation topic item in step S2303.

In the above example, the information on the topic articles of the content preferred by the user of the computing device 100 may be included in the context information based on the user of the computing device 100.

A content topic article that is primarily generated can be configured to be detected based on the frequency of content generation (or generation number). For example, if five content snippets are generated for a coffee topic, and ten content snippets are generated for a dating topic, and 13 content snippets are generated for a meeting topic, and two Content snippets are generated with respect to a game theme, and a reference value is 3, the computing device 100 can detect coffee, quotes and meeting as content theme articles that are primarily generated.

The content topic articles that are primarily generated can be configured to detect n snippets of the main topic articles based on the frequency of content generation. For example, if five content snippets are generated for a coffee topic, and ten content snippets are generated for a dating topic, and 13 content snippets are generated for a meeting topic, and two snippets of content are generated with respect to a game theme, and n is 2, the computing device 100 can detect meetings and appointments as content theme articles that are primarily generated.

At step S2304, computing device 100 provides the detected recommendation topic article. A recommendation topic article may be provided as shown on a display 2203 illustrated in FIG. 22, but exemplary embodiments are not limited thereto. Fig. 25 illustrates an example of a recommendation topic article display system according to an exemplary embodiment. Fig. 25 illustrates that the recommendation topic articles are provided as a 2500 list.

At step S2305, computing device 100 receives a select signal that selects a topic item. A select signal indicates a user input indicating a selection. The display 2203 illustrated in Fig. 22 and Fig. 25 show an example where a select signal is received that selects a TH1 item item.

In step S2306, computing device 100 generates and records content. In step S2305, when a select signal is received that selects a topic item, computing device 100 may provide an input window 2600 to generate new content as illustrated in Fig. 26. Fig. 26 illustrates an example of a screen including the input window 2600 for generating new content according to an exemplary embodiment.

Referring to Fig. 26, the input window 2600 may include a display window 2601 showing a selected item item 2602, a title item entry window 2603 selected item 2602, an image input window 2604 related to article 2602 of selected topic, a video input window 2605 related to article 2602 of selected topic, an audio input window 2606 related to article 2602 of selected topic, a text input window 2607 related to article 2602 of selected topic, and article 2608 to request the exchange of new content, including input information, but not limited to the configuration of Fig. 26.

When one of the input windows 2603 to 2607 included in the input window 2600 is selected, the computing device 100 may provide a window (eg, a virtual keyboard) for inputting information according to the type of inputtable information, but not is limited to them. For example, when one of input windows 2603 to 2607 is selected, computing device 100 may provide a window to request execution of a related application. When one of input windows 2603 to 2607 is selected, computing device 100 can run a related application.

For example, when image input window 2604 is selected, computing device 100 may provide a window to request the execution of an album application or a camera application. When the image input window (eg, photo) 2604 is selected, the computing device 100 can execute a camera application to immediately execute a photography mode. An operation of the computing device 100 in accordance with the selection of the image input window 2604 can be set or changed using an environment setup menu.

When the video input window 2605 is selected, the computing device 100 may provide a window to request the execution of a video application or a camera application. When the video input window 2605 is selected, the computing device 100 can run a video application to provide a screen for selecting a video to be managed. When the video input window 2605 is selected, the computing device 100 can execute a camera application to immediately execute a video photography mode. An operation of the computing device 100 in accordance with the selection of the video input window 2605 can be set or changed using an environment setup menu.

When the voice input window 2606 is selected, the computing device 100 may provide a window to request the execution of a voice recording application. When the voice input window 2606 is selected, the computing device 100 can run a voice recording application to immediately perform the recording. An operation of the computing device 100 in accordance with the selection of the voice input window 2606 can be set or changed using an environment setup menu.

When text input window 2607 is selected, computing device 100 may provide a window to request the execution of a virtual keyboard or a pen input. When text input window 2607 is selected, computing device 100 can execute a virtual keyboard. When text input window 2607 is selected, computing device 100 can execute a pen input. An operation of the computing device 100 according to the selection of the text input window 2607 can be set or changed using an environment setup menu.

In step S2306, computing device 100 can record new generated content by mapping geographic location information and information about generated content.

Fig. 27 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 27 illustrates an example where, regardless of whether a request to generate content is received, a recommendation topic item based on geographic location can be provided as notification as personalized information, and new content generated from according to the recommendation topic article provided.

Operations S2701, S2702, S2704 and S2705 illustrated in Fig. 27 are respectively performed similarly to operations S2302, S2303, S2305 and S2306 in Fig. 23 described above. Operation S2701 is performed even when a request to generate content is not received.

When a recommendation topic article is detected in operation S2702, computing device 100 displays the recommendation topic article as a notification in operation S2703.

Figs. 28a and 28b illustrate screens 2810 to 2860 showing a recommendation topic article as notification.

Screen 2810 of Fig. 28a shows an example notification of a recommendation topic article 2802 using a notification bar 2801 of computing device 100. When recommendation topic article 2802 is detected, computing device 100 automatically expands notification bar 2801 located at the top end of a screen to notify detection of recommendation topic article 2802.

With reference to screen 2810 of Fig. 28a, information such as "SHORTCUT TO GENERATE NEW CONTENT" can be displayed adjacent to article 2802 of recommendation topic. When "SHORTCUT TO GENERATE NEW CONTENT" is touched, computing device 100 may provide input window 2600 to generate new content as illustrated in FIG. 26. When "SHORTCUT TO GENERATE NEW CONTENT" is touched, it may indicate that recommendation topic article 2802 is selected. "SHORTCUT TO GENERATE Nu Ev O CONTENT" may be expressed as "SHORTCUT TO PUBLISH", but is not limited thereto.

Screen 2820 of Fig. 28a is an example of notification of a recommendation topic article using a popup window 2803. The pop-up window 2803 may include the recommendation topic article 2802, a message to verify if new content is generated, and an article (Yes, No) through which the verification message can be replied to. When an "Yes" answer item is selected, the computing device 100 can close the popup window 2803 and provide the input window 2600 to generate new content, as illustrated in FIG. 26. The "Yes" answer item is selected indicates that article 2802 of the recommendation topic is selected. When the answer item "No" is selected, the computing device 100 closes the popup window 2803.

Screens 2810 and 2820 of Fig. 28a can be provided independently of an application that is currently being run by computing device 100.

A screen 2830 of FIG. 28a is an example of a notification topic article 2802 notification based on a portion of a service application run screen 2804. The service application includes a function of generating new content based on a geographical location. The service application may include, but is not limited to, but is not limited to, but is not limited to, a navigation application, a video call application, a social network service application, a life registration application, and a life application.

When the recommendation topic article 2802 is touched on the screen 2830, the computing device 100 provides the input window 2600 to generate new content as illustrated in Fig. 26. Touching the recommendation topic article 2802 indicates that Article 2802 of recommendation topic has been selected.

Screens 2840 to 2860 of Fig. 28b illustrate an example of notification of a plurality of articles 2802 and 2805 of recommendation topic.

When referring to the screen 2840 of FIG. 28b, the computing device 100 expands a notification bar region 2801 in accordance with the number of articles 2802 and 2805 of recommendation topic. When referring to the screen 2850 of Fig. 28b, the computing device 100 provides popup windows 2803 and 2806 corresponding to the number of articles of recommendation 2802 and 2805. When referring to the screen 2860 of Fig. 28b, the computing device 100 provides icons corresponding to the number of articles 2802 and 2805 of recommendation topic.

A procedure for notifying the plurality of articles of recommendation 2802 and 2805 is not limited to screens 2840 to 2860 of Fig. 28b.

Fig. 29 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. In an example procedure in Fig. 29, a content registration operation is added to a procedure in Fig. 23.

Operations S2901 to S2906 of Fig. 29 are respectively performed similarly to operations S2301 to S2306 of Fig. 23. When a request is received to transmit recorded content to computing device 100 in operation S2907, computing device 100 transmits the recorded content to a 2900 server.

The computer device 100 may further display an input window 3001 for making the generated content public and an input window 3002 for sharing the generated content illustrated in FIG. 30, when the share 2608 in FIG. 26 is touched after content is generated.

Fig. 30 illustrates an example of a screen where the exchange of generated content can be configured, according to an exemplary embodiment. Based on an article-based user input such as public, visible only to friends, and visible only to me provided through the input window 3001 to make the generated content public, the computing device 100 can set a publishing range of the generated content. According to the input of information about social networks by using the input window 3002 to share the generated content, the computing device 100 can determine the social networks through which the generated content should be shared.

Server 2900 can be determined based on information input through input window 3002 to share the generated content. For example, when Chat On is entered through input window 3002, server 2900 may be a Chat On server. When KakaoTalk is entered through input window 3002, server 2900 may be the KakaoTalk server. When Routrip is entered through input window 3002, server 2900 can be a Routrip server.

The input window 3001 for publishing the generated content can be expressed as an input window for publication. Furthermore, while the content being streamed may be new content currently generated, a plurality of content may also be streamed to the 2900 server in units of days, weeks or months or in units of a geographic location. A unit of transmitted content is not limited to them.

In step S2909, server 2900 records and manages the content received in step S2909.

Fig. 31 is an operational flow chart of a procedure for providing personalized information in accordance with an exemplary embodiment. Fig. 31 illustrates an example of providing a recommendation article in the form of notification as personalized information without a user request to generate content. A server 3100 of Fig. 31 is a server that is capable of obtaining and providing information about geographic locations like a map server. Server 3100 may include server 700 illustrated in FIG. 7.

In step S3101, computing device 100 obtains context information based on the user. In step S3102, server 3100 obtains context information based on geographic location. Contextual information based on geographic location may be expressed as information based on geographic location as described above in this disclosure.

Step S3102 can be performed before step S3101 or it can be performed continuously independently of computing device 100.

When the user-based context information obtained from the computing device 100 is received, the server 3100 detects a recommendation topic article using the received user-based context information and the geographic location-based context information in the operation S3104. Detection of a recommendation topic article can be performed as in step S2303 of Fig. 23 described above.

When at least one recommendation topic article is detected, server 3100 transmits information about recommendation topic articles to computing device 100 in step S3105. The computing device 100 provides a recommendation topic article as a notification based on the topic article of recommendation received in operation S3106. The notification can be provided as illustrated on screens 2810 to 2860 in Figs. 28a and 28b, but is not limited thereto.

When a select signal is received that selects a recommendation topic item provided as notification in step S3107, computing device 100 generates content in step S3108 and transmits the content generated to server 3100 in step S3109. Then, the server 3100 records the received content and manages it in step S3110. Content registration may include, but is not limited to, mapping a topic article to the content received and a geographic location.

Fig. 32 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. The procedure of Fig. 32 includes an operation of providing a recommendation topic article as personalized information according to a user's request to generate content, and an operation of registering and managing the generated content to the 3100 server based on the article. of recommendation topic provided.

Operations S3202 to S3211 of Fig. 32 can be performed respectively in the same way as operations S3101 to S3110 of Fig. 31 described above. Step S3201 of Fig. 32 can be performed in the same manner as step S2301 of Fig. 23 described above.

Fig. 33 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. FIG. 33 illustrates an example of a recommendation topic article notification based on contextual information based on geographic location obtained by server 3100, context information based on user obtained by computing device 100, and a profile of Social networks of the user of the computing device 100 received from a social network service server (SNS) 3300, as personalized information.

In step S3301, user-based context information (except social network profile information) is obtained from the user of computing device 100.

Operations S3302, S3303 and S3306 to S3311 in Fig. 33 can be performed respectively in a similar way to operations S3102, S3103 and S3105 to S3110 in Fig. 31.

In step S3304, when social network profile information is received from the SNS server 3300, the server 3100 detects a recommendation topic article based on the user-based context information received from the computing device 100, the context-based information in the geographical location obtained by the server 3100, and the information of the social network profile of the user of the computing device 100 received from the 3300 SNS server.

For example, when information about a current location and current time from computing device 100 (eg, store A at Gangnam station, 7 pm) is included in the user-based context information received from computing device 100 and a topic article (eg, drinking, eating, and dining together) of the content generated at the current location of the computing device 100 is included in the context information based on the geographic location, and the information (eg, drinking in the afternoon ) About the user preference of the computing device 100 is included in the social network profile information, the server 3100 can detect alcohol consumption as a recommendation topic item in step S3305.

The 3300 SNS server is a social media server. For example, the 3300 SNS server may be one of a Routrip server, a Facebook server, a Twitter server, a blog server, a YouTube server, a LinkedIn server, and / or the like, but is not limited to themselves.

In step S3304, the 3300 SNS server can transmit a history of social network service to the 3100 server. In this case, in step S3305, the 3100 server can detect a recommendation topic article based on the history of the network service. , and the user-based context information obtained in the operation S3301 may include context information, from which the history of the social network service is excluded.

Fig. 34 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. Fig. 34 is an example of providing a recommendation topic article detected based on user-based context information obtained by computing device 100 and a user's social media profile of computing device 100 received from 3300 SNS server , as personalized information.

Operations S3401 to S3403 can be performed similarly to operations S3301, S3303, and S3304 in Fig. 33, and operations S3405 to S3410 can be performed similarly to operations S3306 to S3311 in Fig. 33.

The user-based context information of the computing device 100 obtained in step S3301 may include context information without a social media profile of the user of the computing device 100. If the information transmitted from the 3300 SNS server is a history of the social network service, the User-based context of the user of computing device 100 obtained in step S3301 may not include the history of the social network service of the user of computing device 100.

In step S3404, server 3100 can detect a recommendation topic article based on user-based context information received from computing device 100 and social media profile information received from SNS server 3300.

For example, when information (eg, Store A at Gangnam Station, 6 pm) about a current location and a current time from computing device 100 is included in the user-based context information received from computing device 100 , and information (eg, a blogger to provide information about a place that has tasty food) about a user preference of the computing device 100 is included in the social network profile information, the server 3100 can detect a food restaurant tasty (or gourmet restaurant) as a recommendation topic item in step S3404.

Fig. 35 is a view illustrating a procedure for providing personalized information in accordance with another exemplary embodiment.

Referring to FIG. 35, a computing device 3501 obtains context information based on user A 3502 and provides it to a map server 3503. The computing device 3501 can transmit location information included in the user-based context information A 3502 to a location-based service (LBS) server 3504. Location information may be obtained by computing device 3501 or may also be entered by the user of computing device 3501. The computing device 3501 can be configured into a device similar to the computing device 100.

Another computing device 3505 obtains context information based on user B 3506 and provides it to map server 3503. The other computing device 3505 may transmit location information included in the user-based context information B 3506 to the location-based service server 3504. The location information may be obtained by another computing device 3505 or may also be entered by the user of the other computing device 3505. The other computing device 3505 can be configured similarly to the computing device 100.

Location based service server 3504 may transmit geographic location based context information based on location information received from user A computing device 3501 3502 and location based context information to location map server 3503. the location information received from the other computing device 3505 of user B 3506.

Map server 3503 may provide user A 3502 with map information 3510 that is customized to user A 3502 based on user-based context information received from computing device 3501 and context information based on the geographic location of the user. user A 3502 transmitted from location based service server 3504.

For example, if the location information transmitted by computing device 3501 to location-based service server 3504 is Manhattan, New York, location-based service server 3504 transmits location-based context information about Manhattan, New York, to map server 3503.

Map server 3503 analyzes user-based context information A 3502 received from computing device 3501. As a result of the analysis, if user A 3502 is a blogger for a tasty food restaurant, and the topic articles that user A 3502 prefers are TH1 (for example, show) and TH3 (for example, dating), the server Map 3503 can provide the computing device 3501 with map 3510, in which tasty food restaurants (for example, tasty food restaurant with shows and / or tasty food restaurants suitable for dating), where TH1 and TH3 are Registered, are marked as points of interest, among the topic articles included in the contextual information based on the geographical location received from the location-based service server 3504.

For example, if the location information transmitted by the other computing device 3505 to the location-based service server 3504 is New York, Manhattan, the location-based service server 3504 transmits geographic location-based context information about New York. , Manhattan to map server 3503.

The map server 3503 analyzes the user-based context information B 3506 received from the other computing device 3505. As a result of the analysis, if user B 3506 is getting married, and the content topic articles that user B 3506 has recently generated are mostly TH2 (eg hotel) and TH5 (eg travel), the map server 3503 can provide the other computing device 3505 with the map 3520 in which the places where TH2 and TH5 (for example, hotels or places to see) are registered, are marked as points of interest, among the topic articles included in the geographic location-based context information received from the location-based service server 3504.

Maps 3510 and 3520 illustrated in Fig. 35 may include point of interest change article 1101 or point of interest information adjustment article 1102 illustrated in Fig. 11. When change article 1101 POI or POI information adjustment item 1102 are included on maps 3510 and 3520, computing devices 3501 and 3505 can change the points of interest marked on maps 3510 and 3520 according to an input from the user based on article 1101 change point of interest or article 1102 adjustment of point of interest information.

The map server 3503 illustrated in Fig. 35 can operate in connection with a mapping application installed on computing devices 3501 and 3505.

Fig. 36 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. FIG. 36 illustrates an example of providing geographic information including POI information as personalized information as a geographic information request is received from a user of computing device 100.

When a request for geographic information is received in operation S3601, computing device 100 obtains at least one of context information based on the user of computing device 100 user and context information based on geographic location in operation S3602. The geographic information request may be received as the request to generate content received in step S2301 of Fig. 23. The operation of computing device 100 in step S3602 may be similar to the operation of computing device 100 in step S2302 of Fig. . 2. 3.

Before requesting geographic information in step S3601, the user of computing device 100 may select in advance a topic item that the user prefers. An operation to select a topic article in advance can be included in an operation to set a filtering condition of the topic article.

Fig. 37 illustrates an example of a screen for selecting a theme item according to an exemplary embodiment. Referring to Fig. 37, computing device 100 may provide a display 3700 including item items TH1 through TH25 as a display through which item items can be selected. Theme articles TH1 through TH25 displayed on the 3700 screen may be theme articles that are frequently used by the user.

The number of selectable topic articles may be greater than a number of TH1 to TH25 topic articles marked on the 3700 screen. If the number of selectable topic articles is greater than the number of TH1 to TH25 topic articles displayed in screen 3700, computing device 100 may provide other theme items by moving a page to the left or right according to a touch input such as a swipe. A procedure for providing other topic articles is not limited to the above procedure. For example, computing device 100 may provide other theme items by moving a page up or down based on a touch input such as a scroll.

A skip article illustrated in Fig. 37 indicates an input article that can be selected if a user wants to skip the preferred topic article selection operation and continue without selecting preferred topic articles. A full article illustrated in Fig. 37 indicates an entry article indicating completion of selection of a preferred topic article. The computing device 100 may provide a screen for selecting POI information illustrated in FIG. 14 described above in lieu of screen 3700 related to the selectable subject items illustrated in FIG. 37.

Fig. 38 illustrates an example of a screen for setting a filtering condition of topic articles according to an exemplary embodiment. Referring to Fig. 38, a topic article filtering condition may include, but is not limited to, information about a time period, a topic article, and distance.

A period illustrated in Fig. 38 indicates a time period prior to the current date. For example, when three days are selected in a period area 3810 as illustrated in FIG. 38, the computing device 100 may perceive the period as three days before the current date.

At least one topic article selected in a topic article area 3820 illustrated in FIG. 38 may indicate a topic article preferred by the user of computing device 100. For example, when a topic article TH1 is selected in topic area 3820 as illustrated in Fig. 38, topic article TH1 may be set as a topic article preferred by the user of computing device 100.

A distance illustrated in FIG. 38 may indicate a radial distance from a current location of computing device 100 or from a location set by the user of computing device 100. For example, when a distance of 10 km is selected in a distance area 3830 as illustrated in FIG. 38, computing device 100 may provide information about a point of interest within 10 km from a reference location.

The computing device 100 can individually control the period area 3810, the item item area 3820 and the distance area 3830. In each of the period areas 3810, topic items area 3820, and distance area 3830, when a touch input such as a slip is received, the computing device 100 can establish a desired filtering condition by moving left or right corresponding to at least one from the period area 3810, the topic item area 3820 and the distance area 3830. When a tactile input is received as an offset in the period area 3810, the topic items area 3820 and the distance area 3830, the computing device 100 can establish a desired filtering condition by moving the area 3810 up or down. of period, the topic articles area 3820 and the distance area 3830 respectively.

Whereas, in step S3603, computing device 100 detects point of interest information based on context information obtained in step S3602. The computing device 100 can detect POI information in the same manner as, but is not limited to, the map server 3503 as described with reference to FIG. 35. For example, computing device 100 may request map server 3403 to detect POI information, and may receive POI information from map server 3503.

When point of interest information is detected, the computing device 100 provides geographic information including the point of interest information in step S3604. The computing device 100 can provide the geographic information including the point of interest information as illustrated in Fig. 39 or Fig. 40.

Fig. 39 illustrates an example of a map image, in which a subject item according to an exemplary embodiment is marked at a point of interest.

Referring to Fig. 39, computing device 100 provides a map image 3900 showing TH1, TH2, TH3 and TH4 subject items at points of interest, as point of interest information.

Fig. 40 illustrates an example of a screen showing an augmented reality (AR) image and information about a point of interest, which are combined together, according to an exemplary embodiment. Referring to Fig. 40, computing device 100 provides a screen on which point of interest information is combined with a 4000 AR image. The 4000 AR image can be obtained using a camera included in the computing device 100. The POI information marked in Fig. 40 may include, but is not limited to icons, comment average, and a representative image. For example, POI information may also include, but is not limited to icons that indicate the store name and amount of customer feedback. Icons can indicate topic articles related to a point of interest. The average of comments can indicate a degree of revision on the point of interest. The representative image may be a representative image of the point of interest.

When an input is received from the user who selects an icon 4001, the computing device 100 may provide a window 4010 that includes a message 4011 recommending nearby locations, an image 4012 representative of the recommended locations, and a summary and explanation 4013 of the locations recommended, illustrated in Fig. 40. The computing device 100 may display window 4010 as a separate pop-up window apart from a window 4004. Window 4004 may include an icon 4001, an average 4002 of comments and / or a representative image 4003 .

The computing device 100 can also individually manage the message to recommend nearby locations 4011, the image 4012 representative of the recommended locations, and the summary and explanation 4013 of the recommended locations, included in window 4010 as separate windows. When a selection of summary and explanation 4013 of the recommended places is received, and the recommended place is a restaurant, the computing device 100 can provide, for example, menus, today's highlight menus, daily specials, happy hour specials and price information through the corresponding window or another independent window.

Fig. 41 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. FIG. 41 illustrates an example of providing geographic information based on user-based context information obtained using computing device 100 and context-based context information obtained by server 4100 as personalized information.

In step S4101, when a request for geographic information is received, the computing device 100 obtains context information based on the user. The geographic information request can be received by designating a specifically designated point as illustrated in Fig. 24 (point A 2401), but a procedure for requesting geographic information is not limited to this.

For example, location information can be entered using a text entry window provided by computing device 100, and computing device 100 can receive the geographic information request through a touch input by selecting a full entry item or a article corresponding to the geographic information request, provided by the computing device 100.

A request to run a mapping application installed on computing device 100 can also be used as a request for geographic information. A procedure for requesting geographic information may be determined by, but is not limited to, an environment setting of the computing device 100 or an environment setting of the map application.

In step S4102, computing device 100 obtains context information based on the user. The computing device 100 may obtain different pieces of user-based context information according to a usage environment and / or specifications of the computing device 100. For example, if computing device 100 is capable of receiving a detection value from an IoT sensor, computing device 100 may obtain context information based on the user using the detection value of the IoT sensor. If the computing device 100 cannot receive a detection value from an IoT sensor, the computing device 100 can obtain context information based on the user regardless of the detection value from an IoT sensor.

The computing device 100 transmits the user-based context information obtained to the server 4100 in step S4103. Server 4100 obtains context information based on geographic location based on user based context information received in step S4104. For example, if the location information indicating New York, Manhattan is included in the received user-based context information as shown in Fig. 35, the 4100 server may obtain context information based on geographic location about New York, Manhattan. Server 4100 may be a server capable of providing a location-based service and a map service, but is not limited thereto.

In step S4105, server 4100 can detect point of interest information based on the obtained geographic location based context information and the received user based context information. For example, computing device 100 may detect information about a point of interest (eg, a point of interest in New York, Manhattan) based on a location profile (eg, information about a topic article registered at a location ) included in context information based on geographic location and a user profile (for example, information about a preferred topic article) included in context information based on the user.

In operation S4106, server 4100 can transmit geographic information including the detected information about a point of interest to computing device 100. After mapping the detected information about a point of interest and the geographic location, the server 4100 can transmit to the computing device 100 the information obtained by mapping the information about a point of interest and the geographic information.

In step S4107, computing device 100 provides the geographic information received from server 4100.

Fig. 42 is an operational flow chart of a procedure for providing personalized information in accordance with another exemplary embodiment. The procedure in Fig. 42 illustrates an example that adds an additional service execution operation to the procedure in Fig. 41.

Operations S4201 to S4207 in Fig. 42 can be respectively performed in a similar way to operations S4101 to S4107 in Fig. 41.

In step S4208, computing device 100 executes an additional service based on the geographic information provided. Additional service may include, for example, booking a designated place online, making a call to a designated place, transmitting a message to a designated place, posting information about a designated place to the 3400 SNS server or blog, and connecting to to a Uniform Resource Locator (URL) connected to, but not limited to, a designated location.

The add-on service may include an immediate-run operation of an application to run the add-on service.

For example, when selecting to make a call to the designated location, the computing device 100 may execute a telephone application and perform a call making operation using a telephone number of the designated location. When the designated place online reservation is selected, the computing device 100 can access the address of a designated place home page by running an Internet application and can open an online reservation page. When information about the designated place is published on the 3400 SNS server or a blog is selected, the computing device 100 can immediately publish the information about the designated place by accessing the 3400 SNS server or blog. When the connection to a URL connected to the designated place is selected, the computing device 100 can immediately perform a connection operation based on the URL connected to the designated place. If there are multiple URLs connected to the designated location, computing device 100 can provide a display by connecting to a URL that is selected from a plurality of URLs, or it can provide a multiple display by simultaneously connecting to multiple URLs.

FIG. 43 is a functional block diagram of computing device 100 used in accordance with exemplary embodiments. Referring to FIG. 43, computing device 100 may include a context information fetching unit (eg, context information fetcher) 4310, a controller 4320, a user interface unit (eg, user interface). user) 4330, a memory 4340 and a communication unit (eg communicator) 4350.

Not all elements of the computing device 100 illustrated in FIG. 43 are necessary elements. The computing device 100 may include more or fewer elements than those illustrated in FIG. 43. For example, the computing device 100 may be configured as illustrated in FIG. 44 to be described later. Device 100 The computer may include a user location information retrieval unit (eg, location finder, location tracker) 4311, a controller 4320, a user interface unit 4330, a memory 4340, and a communication unit 4350.

The context information obtaining unit 4310 can obtain at least one of the context information based on the user of the user of the computing device 100 described with reference to the operation S2302 of Fig. 23 and the context information based on the geographical location described with reference to step S3102 of Fig. 31. Obtaining geographic location based context information can be expressed as receiving geographic location based context information.

To obtain user-based context information and geographic location-based context information, the context information retrieval unit 4310 may include at least one item that is connected to at least one of the sensors included in a unit sensor (eg sensor group) 4460, a camera 4490, and the communication unit 4350 illustrated in FIG. 44 for transmitting or receiving data.

To obtain the user-based context information and the geographic location-based context information, the context information retrieval unit 4310 may include an element that obtains the user-based context information (eg, a first context information retrieval unit) and an element that retrieves context information based on geographic location (eg, a second context information retrieval unit). The context information obtained by the context information obtaining unit 4310 is transmitted to the controller 4320.

Information about topic articles included in context information can include a content topic article generated in a geographic location, the number of times a topic article is generated, and the priority information of a topic article based on but not limited to the number of times a topic article is generated.

Information about topic articles can include, for example, topic articles and the number of times a topic article is generated, such as 10 times from topic A (for example, citations) of content generated in place A (by example, coffee), three times from topic B (for example, meeting), once from topic C (for example, study). Information on a topic article may include priority information on topic articles, such as the first topic for rating A, a second topic for rating B, and a third topic for rating C.

The geographic location-based context information may be obtained from an application that provides geographic location information (eg, a mapping application) stored in memory 4340. For example, the context information retrieval unit 4310 may request to the application that provides geographic location information stored in memory 4340 contextual information based on geographic location about point A, and may receive geographic location information from the application that provides geographic location information about point A. For this Finally, the context information obtaining unit 4310 can transmit or receive data directly to or from memory 4340, but it can also transmit or receive data to or from memory 4340 through controller 4320.

Controller 4320 can communicate with a server that provides geographic location information (for example, the map server or a location-based service (LBS) server 3504, etc.) connected through the 4350 communication unit to update the geographic location information provided by the application stored in 4340 memory.

The context information retrieval unit 4310 may receive context information based on geographic location from a location management server (eg, a management server installed at location A). For example, if the computing device 100 is tagged in an NFC tag installed at location A, the context information retrieval unit 4310 may receive information about a geographic location with respect to location A from the NFC tag through the unit. 4350 communication. For this, the context information obtaining unit 4310 may include an element to access an NFC communication module included in the communication unit 4350. The NFC communication module can read information from an NFC tag and write information to the NFC tag.

The context information retrieval unit 4310 may receive geographic location context information from an external device (eg, another person's computing device) connected to the computing device 100 through the communication unit 4350. For example, context information retrieval unit 4310 may receive context information based on geographic location stored in another person's computing device that is connected to computing device 100, based on Bluetooth communication using communication unit 4350.

The context information retrieval unit 4310 can obtain context information based on geographic location based on a user input received from a user input unit 4332. For example, context information retrieval unit 4310 may receive information about a topic item that a user has entered directly through user input unit 4332 at location A as context information based on geographic location with regarding place A.

Context information retrieval unit 4310 may obtain user-based context information by receiving information about a user (eg, user life record information), stored in memory 4340, and / or information about a user from an external device (for example, an SNS server, a handheld device such as a smart watch, a user information management server, a user information database, etc.) connected to the computing device via the 4350 communication unit. However, the procedure for obtaining user-based context information is not limited to this.

The context information retrieval unit 4310 may include a user location information retrieval unit 4311. User location information obtaining unit 4311 can detect whether the user of computing device 100 has moved, and can obtain physical location information.

The user location information obtaining unit 4311 can obtain user location information using at least one of a value detected by at least one sensor included in the computing device 100, a GPS satellite signal and / or location information of net.

The user location information gathering unit 4311 may include at least one sensor (for example, a motion detection sensor, an illuminance sensor, an accelerometer sensor, a geomagnetic sensor, a gyroscope, a position sensor, etc.) included in the sensor unit (eg sensor group) 4460 illustrated in Fig. 44 to be described later, a camera 4490 and / or at least one element that can transmit or receive data to or from at least a communicator included in a 4450 communication unit.

User location information obtained using user location information obtaining unit 4311 is transmitted to controller 4320.

Controller 4320 can detect whether a user's location has been moved based on user location information provided from user location information obtaining unit 4311. By detecting if the user's location is moved, the 4320 controller can track the user's location. By tracking user location, controller 4320 can variably control a user location measurement interval by user location information gathering unit 4311.

The controller 4320 can detect a movement speed, movement time and / or movement distance of the user of the computing device 100 as a function of the information received from the user location information obtaining unit 4311.

Controller 4320 can variably control a user location measurement interval by user location information gathering unit 4311 in accordance with at least one of the detected movement speed, movement time and movement distance of the user. user of computing device 100 based on information received from user location information obtaining unit 4311. Controller 4320 can obtain information about a user's initial route based on user location information obtained from user location information obtaining unit 4311.

Controller 4320 can detect information indicating the user's expected route based on information about a user's initial route from the user's location history information. The user's location history information can be stored in memory 4340 but can also be received from an external device through the 4350 communication unit. The external device may include, but is not limited to, the server 700 in FIG. 7.

When information indicating the intended route of the user is detected, the controller 4320 can variably control a user location measurement interval performed by the user location information gathering unit 4311 in accordance with at least one of the detected movement speed, movement time and / or information from the user's surrounding environment.

If the user's predicted route based on the user's initial route is not detected from the user's location history information, the 4320 controller can variably control a user location measurement interval by the 4311 unit. obtaining user location information based on at least one of a movement speed and / or information from the user's surrounding environment.

Controller 4320 can obtain route information based on user location information transmitted from user location information retrieval unit 4311, and update user location history information based on information obtained about a route. If the user location history information is stored in memory 4340, controller 4320 can update the user location history information stored in memory 4340. If user location history information is stored on server 70 The controller 4320 may transmit information about the information obtained about the route of a user to the server 700 and request to update the information of the user's location history.

Controller 4320 may perform an operation based on at least one of the operating flow diagram of computing device 100 in accordance with one or more exemplary embodiments, as illustrated in Figs. 2, 3, 4, 6, 7, 9, 10, 12, 15, 17-20, 23, 27, 29, 31-34, 36, 41 and 42.

Controller 4320 may be mentioned as a processor that controls an operation of computing device 100. Controller 4320 can detect at least one recommendation topic article based on context information received from context information retrieval unit 4310. For example, if information about place A (10, 3, 1) and information about user A (10, 0, 0) are included in the received context information, controller 4320 can detect a topic article with the number 10 in the information about the place A and the information about the information of the user A as an article of recommendation topic.

Information about place A (10, 3, 1) may indicate that a topic article A from the content generated in place A is generated ten times, and a topic article B from the content is generated three times and a topic article C of content is generated once. Information about user A (10, 0, 0) may indicate that a topic item A of user-generated content of computing device 100 is generated ten times, and a topic item B of content is generated zero times and a Content topic article C is generated zero times. If a topic article included in information about place A and a topic article included in information about user A are the same as those described above, the 4320 controller can detect topic article A as a topic article from recommendation.

The 4320 controller can display the detected item item through a display unit (eg, display system) 4331 included in the user interface unit (eg, user interface) 4330. When a select signal that selects the recommendation topic item displayed through the rendering unit 4331 through the user input unit (eg user input) 4332 included in the user interface unit 4330, the controller The 4320 can provide a corresponding graphical user interface (GUI) through the 4331 rendering unit. The corresponding GUI can be used to generate content regarding the selected recommendation topic article. The GUI used to generate content can be as illustrated in Fig. 26, but is not limited to them.

When content generation is completed according to user input using the GUI provided through rendering unit 4331, controller 4320 records the generated content. The content can be recorded in memory 4340 of computing device 100 or recorded in server 2900 illustrated in FIG. 29 or an external device (a user database or other user computing device).

Controller 4320 can detect a point of interest based on context information received from context information retrieval unit 4310. For example, if the context information about location A and the context information about location B are included in the received context information, and the context information about location A indicates location A (10, 3, 1) = place A (article of topic A, article of topic B, article of topic C), and the context information about place B indicates place B (0, 12, 2) = place B (article of topic A, article of topic B and article of topic C), and if user A (10, 0, 0) included in the context information indicates user A (article of topic A, article of topic B and article of topic C), the Controller 4320 detects location A as a point of interest on user A.

Controller 4320 can provide a map that includes points of interest detected through display unit 4331. When a select signal is received that selects one of the points of interest displayed on the rendering unit 4331 through the user input unit 4332, the controller 4320 can provide information based on the selected point of interest through the representation unit 4331. Information based on the selected point of interest may include, for example, a menu to select an additional available service based on the selected point of interest. The additional service may include, but is not limited to, the additional service described in step S4208 of Fig. 42.

The display unit 4331 is configured to display information processed by the computing device 100. The display unit 4331 can display the screens as illustrated in Figs. 1, 5, 8, 11, 13, 14, 16a, 16b, 16c, 21, 22, 24, 25, 26, 28a, 28b, 30, 37, 38, 39 and 40 described above.

When a touchpad and display system are configured in a layered structure as a touch screen, the display unit 4331 can be used as an output device and an input device. The display unit 4331 may include at least one of a liquid crystal display, a thin film transistor liquid crystal display, an organic light emitting diode, a flexible display system, a 3D display system and / or a system electrophoretic representation (EPD).

In accordance with one embodiment of computing device 100, computing device 100 may include two or more display units 4331. The two or more 4331 display units may be arranged facing each other using a hinge.

User input unit 4332 may receive user input based on a screen displayed on display unit 4331. User input unit 4332 may be mounted on computing device 100 so that a user can enter data to control computing device 100.

The user input unit 4332 that can be mounted on the computing device 100 can include, for example, at least one of a keyboard, a dome switch, a touch panel (eg, capacitive overlay, resistive overlay, infrared beam , surface acoustic wave, integral strain gage and type touch panels piezoelectric), a scroll wheel and / or a scroll switch, but is not limited thereto.

User input information that can be entered through user input unit 4332 can include at least one touch-based input information, motion-based input information, vision-based input information and / or input information based on, but not limited to, the user's voice.

For example, touch-based input information can include a tap (or tap), a long tap (long tap), a tap and hold, a tap and drag, a double tap, a drag, a pan, a tap fast, drag and drop, and / or sweep, but is not limited thereto.

The motion-based input information may include, for example, entering information based on a user gesture (eg, shaking a device, rotating a device, and lifting a device) based on a movement of the computing device 100, but not limits them.

Vision-based input information may include information that is recognized by analyzing an input image obtained using a camera embedded in computing device 100 without a contact between computing device 100 and a user.

Memory 4340 can store a program for processing and control by controller 4320. A program stored in memory 4340 can include an operating system (OS) program and various application programs. Various application programs may include, for example, a geographic location information delivery application, a custom information delivery application and / or a user location tracking application, but without limitation.

Memory 4340 stores information managed by an application program. For example, memory 4340 may store content generated in accordance with an exemplary embodiment, information about generated content, context information based on geographic location, context information based on the user of the user of the computing device 100 and / or information from the user. but not limited to the user's location history.

Memory 4340 may include at least one type of storage medium selected from a type of flash memory, a type of hard disk, a type of micro media card, a card type memory (eg, SD or XD memory), a random access memory (RAM), static random access memory (RAM), a read only memory (ROM), erasable and electrically programmable read only memory (EEPROM), a programmable read only memory (PROM), a memory magnetic, a magnetic disk and / or an optical disk.

The computing device 100 can be configured to use web storage or a cloud server that performs a memory storage function 4340 on the Internet. In this case, the web storage or cloud server described above can provide information on a screen shown in the display unit 4331.

Communication unit 4350 may include at least one element for communication between computing device 100 and at least one external device (eg, a handheld device such as a smart watch, a service provider server, another user computing device, or a cloud server, etc.). For example, the communication unit 4350 may include at least one of a short-range communicator 4451, a mobile communicator 4452, and / or a relay receiver (eg, GPS receiver) 4453 illustrated in FIG. 44 below , but the items included in the 4350 communication unit are not limited thereto.

Referring to Fig. 44, computing device 100 may include a controller 4420, a user interface unit (eg, user interface) 4430, a memory 4440, a communication unit (eg, communicator) 4450 , a sensor unit (eg, sensor group) 4460, an image processor 4470, an audio output unit (eg, audio generator) 4480, and a camera 4490.

The computing device 100 may include a battery. The battery may be included within computing device 100 or may be removably connected to computing device 100. The battery can be used to supply power to all the elements included in the computing device 100. The computing device 100 can receive power from an external power device through the communication unit 4450. The computing device 100 may further include a connector that can be connected to the external power device.

Controller 4420, user interface unit 4430, memory 4440, and communication unit 4450 illustrated in FIG. 44 may respectively be referred to as similar or identical elements to controller 4320, user interface unit 4330, memory 4340, and the 4350 communication unit illustrated in Fig. 43.

The display unit (eg, display system) 4431 and the user input unit (eg, User Introducer) 4432 illustrated in Fig. 44 may respectively be called the display unit 4331 and the 4332 input unit. user illustrated in Fig. 43.

The programs stored in memory 4440 can be classified as a plurality of modules according to the respective functions. For example, programs stored in memory 4440 can be classified as a 4441 UI module, a notification module 4442, and an application module 4443, but without limitation. For example, when display unit 4431 is coupled to a touch panel layer, the plurality of modules may include a touch screen module.

The 4441 UI module can provide GUI information about the user path described above with reference to exemplary embodiments and GUI information used to generate new content for the 4420 controller. The 4441 UI module can provide the 4420 controller with a UI or GUI or the like. that is specialized in each application installed in the computing device 100.

Notification module 4442 may generate a signal that notifies the recommendation of a topic item by computing device 100, but a notification generated by notification module 4442 is not limited thereto.

The notification module 4442 can output a notification signal in the form of a video signal illustrated in Figs. 28a and 28b through rendering unit 4431, or may output a notification signal as an audio signal through, but is not limited to, audio output unit 4480. A notification signal in the form of an audio signal can include a notification signal related to the user path illustrated in Fig. 1.

Application module 4443 may include various applications including a custom information delivery application installed on computing device 100. A custom information delivery application in accordance with an exemplary embodiment may operate in connection with other applications configured on the computing device 100. For example, a customized information delivery application for performing an additional service described with reference to step S4208 of FIG. 42 may operate in connection with other applications configured on computing device 100.

Communication unit 4450 may include at least one element for communication between computing device 100 and at least one external device (eg, a service provider server, a cloud server, a handheld device, or an application accessory ). For example, the communication unit 4450 may include, but is not limited to, one of the short range communicator 4451, the mobile communicator 4452 and / or the relay receiver 4453.

Examples of the 4451 Short Range Communicator may include, without limits, a module through which at least one communication between Bluetooth communication, Bluetooth Low Energy Communication (BLE), Near Field Communication, Wi-Fi LAN communication ( WLAN), zigbee communication, Ant + communication, an infrared data association communication (IrDA), Wi-Fi Direct communication (WFD) and / or ultra-broadband communication (UWB). For example, the 4451 short-range communicator may include an IrDA communication module.

The mobile communicator 4452 transmits or receives a wireless signal to or from at least one of a base station, an external device and / or a server via a mobile communication network. The wireless signal may include a voice call signal, a video call signal, or data in various forms according to the transmission and reception of text / multimedia messages.

Relay receiver 4453 receives a broadcast signal and / or broadcast related information through a broadcast channel from the outside. Examples of a transmission channel may include, without limitation, a satellite channel, a terrestrial channel, and / or a radio channel.

The communication unit 4450 can transmit information on at least a piece of content generated by the computing device 100 according to an exemplary embodiment, to an external device or receive at least one of a recommendation topic article, context information based on the geographical location and / or information of the user's location history, from the external device. The information, data, and signals transmitted or received through the communication unit 4450 are not limited to the examples above.

Sensor unit 4460 may include, for example, a proximity sensor 4461 to detect whether a user has approached computing device 100, an illuminance sensor 4462 (or an optical sensor, or an LED sensor) to detect illuminance from a surrounding environment of computing device 100, a microphone 4463 to recognize the voice of the user of computing device 100, a 4464 moodscope sensor to detect the mood of the user of computing device 100, a motion detection sensor 4465 to detect the activity of the user, a position sensor 4466 (eg, a GPS sensor) to detect a location of the computing device 100, a gyroscope 4467 to measure an angle of support of the computing device 100, an accelerometer sensor 4468 to measure an inclination and an acceleration of the computing device 100 with respect to a ground surface and / or a geomagnetic sensor 4469 to detect a bearing angle of the four cardinal points with respect to the computing device 100, but is not limited thereto.

For example, the 4460 detection unit may include a gravity sensor, an altitude sensor, a chemical sensor (eg, an odor sensor), a temperature sensor, a humidity sensor, a barometer, a sensor fine dust, an ultraviolet sensor, an ozone sensor, a carbon dioxide (CO2) sensor, an optical sensor and / or a sensor network (for example, a network based on Wi-Fi, Bluetooth, 3G (Generation), LTE (long-term evolution), NFC).

The detection unit 4460 may include, for example, a pressure sensor (eg, a touch sensor, a piezoelectric sensor, or physical buttons), a status sensor (eg, a headphone terminal or an antenna). DMB), a standard terminal (eg, a terminal capable of recognizing whether charging is performed, a terminal capable of recognizing whether computing device 110 is connected to a personal computer (PC), or a terminal capable of recognizing whether computing device 110 is connected to a port), a time sensor, and / or a health sensor (eg, a biosensor, a heart rate sensor, a blood flow meter, a diabetes sensor, a pressure sensor arterial, a stress sensor, etc.).

Microphone 4463 can receive an audio signal from outside the computing device 100 and convert the received audio signal into an electrical audio signal and transmit it to controller 4420. Microphone 4463 can be configured to perform an operation based on a deletion algorithm. Noise to eliminate noise generated when receiving an external acoustic signal. The 4463 microphone can be called an audio input unit.

A result of the detection detected by the sensor unit 4460 is transmitted to the controller 4420.

Controller 4420 can track a user location of computing device 100 based on a detection value received from sensor unit 4460 (eg, illuminance sensor 4462), detect an initial route based on the location of the tracked user, and detect a user's expected route based on the initial route from the user's location history information.

The 4420 Controller may recommend a topic article. For example, controller 4420 may recommend a topic item (eg, happiness) based on the location information (eg, home) of the detected computing device 100 based on a detection value received from the location sensor 4466 and the information of emotion (eg, happiness) of the user of the computing device 100 detected based on a detection value received from the sensor 4464 moodscope.

Controller 4420 can control a global operation of computing device 100. For example, controller 4420 may execute programs stored in memory 4440 to control general operation of sensor unit 4460, memory 4440, user interface unit 4430, image processor 4470, output controller unit 4480. audio, the 4490 camera and / or the 4450 communication unit.

Controller 4420 may perform an operation based on at least one of the operating flow diagram of computing device 100 in accordance with one or more exemplary embodiments, as illustrated in Figs. 2, 3, 4, 6, 7, 9, 10, 12, 15, 17-20, 23, 27, 29, 31-34, 36, 41 and 42.

Controller 4420 can include a plurality of processors according to an operating environment of computing device 100. For example, controller 4420 may include a processor operating in a low power mode of computing device 100 and a processor operating in a normal mode of computing device 100. Controller 4420 may include a plurality of processors classified according to the elements included in computing device 100.

The image processor 4470 processes the image data received from the communication unit 4450 or stored in memory 4440 so that the image data can be displayed on the display unit 4431. For example, signal processing on image data can be performed such that a screen as illustrated in Figs. 1, 5, 8, 11, 13, 14, 16a, 16b, 16c, 21, 22, 24, 25, 26, 28a, 28b, 30, 37, 38, 39, and 40 are shown in display unit 4431.

The audio output unit 4480 outputs audio data received from the communication unit 4450 or audio data stored in memory 4440. In addition, the audio output unit 4480 can output a sound signal (eg, a beep sound). notification) related to a function performed by the computing device 100. The audio output unit 4480 can output a notification sound with respect to at least one of the notification details illustrated in Figs. 28a and 28b. The audio output unit 4480 may include, but is not limited to, a speaker or buzzer.

Camera 4490 can obtain an image frame such as a still image or video through an image sensor in a video call mode or a photography mode. Camera 4490 can obtain a user finger gesture image from computing device 100 and transmit it to controller 4420. Controller 4420 can use the user finger gesture image described above to determine whether to select a topic item, whether to select cancel content generation, if content generation is complete, or if generated content is registered or published, but the use of the finger gesture image is not limited to this. An image captured using the image sensor can be processed through the 4420 controller or an additional image processor.

An image frame processed by camera 4490 can be stored in memory 4440 or transmitted to the outside through communication unit 4450. The computing device 100 may include at least two cameras 4490 in accordance with a configuration of the computing device 100.

FIG. 45 is a structural diagram illustrating a 4500 system for providing personalized information in accordance with an exemplary embodiment. Referring to FIG. 45, the 4500 system for providing personalized information may include a computing device 100, smart glasses 4510, a smart watch 4520, another 4530 device, a 4540 server, and a 4550 network, but the 4500 system configuration for Providing personalized information is not limited to this.

The smart glasses 4510, the smart watch 4520, and the other device 4530 may be user-owned devices of the computing device 100. For example, when an AR-based image as shown in Fig. 40 is provided through the smart glasses 4510, the content of a selected topic article using the smart glasses 4510 can be generated using the computing device 100.

Selection of a theme item using the 4510 smart glasses can be done, for example, by using, but is not limited to, an eye tracking procedure. When one of the displayed item items is selected using the eye tracking procedure, the information about the selected item item can be transmitted to the computing device 100. In this way, computing device 100 can display a GUI screen as illustrated in FIG. 26.

When a theme item is selected using the 4510 smart glasses, the 4510 smart glasses can display the GUI screen as shown in Fig. 26. When the GUI screen as shown in Fig. 26 is displayed on the 4510 smart glasses , the smart glasses 4510 can generate content according to a received user input using a user input unit or a microphone of the smart glasses 4510.

For example, the smart 4510 glasses can perform operations such as moving the selection information displayed on the smart 4510 glasses by the gesture of a user to a desired topic item, displaying a GUI screen to generate new content as shown in Fig. 26 based on the number of times the eyes blink, return to a previous screen, cancel a content generation operation, or convert to another operating mode.

Smart glasses 4510 and smart watch 4520 can transmit detection values such as a user's health condition or information to computing device 100. The condition of a user may include, but is not limited to, for example, information about user fatigue obtained through the use of an image sensor included in the 4510 smart glasses. Health information may include, for example, a heart rate, blood sugar, and / or body temperature obtained through the use of, but is not limited to, the biological sensor included in the 4520 smart watch described above.

The computing device 100 may recommend a topic item using a detection value received from the smart glasses 4510 and / or the smart watch 4520, or provide information about a point of interest adjacent to a user's route.

When the other device 4530 is a user's desktop computer, the other device 4530 can record and manage the content transmitted by the computing device 100 based on a geographic location. Furthermore, the other device 4530 may provide the computing device 100 with information about the content recorded at a geographic location in accordance with a request from the computing device 100.

The other device 4530 may be a computing device of a user other than the user of computing device 100 or may include a handheld device of a user who is with, but is not limited to, the user of computing device 100. For example, the other device 4530 may include the car 1800 in Fig. 18 or other computing devices 1900 and 2000 in Figs. 19 and 20.

If the other device 4530 is a smart watch of a person who is with the user of the computing device 100, and the health information of a person who is with the user of the computing device 100 is received from the smart watch, the computing device 100 may recommending a topic article based on the health information of the person who is with the user of computing device 100.

For example, if the other device 4530 is a computing device (eg, a smartphone, a desktop computer, etc.) of a person who is with the user of the computing device 100, the computing device 100 may receive from the other device 4530 geographic location-based context information (eg, information on a topic article recorded by the person who is with the user of the computing device 100 based on the geographical location) of the person who is with the user of the device 100 computer, and recommend a topic article using information about the topic article received.

The use of the other 4530 device is not limited to the examples above.

Server 4540 may include at least one of a cloud server of the user of computing device 100, server 700 illustrated in Figs. 7, 9, 10, 12, 15, and 17, the 2900 server described with reference to Fig. 29, the 3100 server illustrated in Figs. 31,32 and 33, the 4100 server described with reference to Figs. 41 and 42, and / or the 3300 SNS server described with reference to Figs. 33 and 34, but is not limited thereto.

Network 4550 can be configured to transmit or receive data using at least one of the communication procedures described with reference to the communication unit 4450 illustrated in FIG. 44, but the configuration of network 4550 is not limited to this.

One or more exemplary embodiments can also be performed as computer readable codes on a computer readable recording medium. The computer-readable recording medium can be any data storage device that can store data that can then be read by a computer system. Examples of the computer-readable recording medium include read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tapes, floppy disks, optical data storage devices, etc. The computer-readable recording medium can also be distributed through network-attached computer systems so that the computer-readable code is stored and executed in a distributed manner.

It should be understood that the exemplary embodiments described herein are to be considered in a descriptive sense only and not for purposes of limitation. Descriptions of features or aspects within each exemplary embodiment should typically be considered as available for features or similar aspects in other exemplary embodiments.

While one or more exemplary embodiments have been described with reference to the figures, it should be understood by those skilled in the art that various changes in form and detail can be made without departing from the scope as defined in the following claims.

Claims (15)

1. A computing device (100) comprising: a location finder (4311) configured to obtain location information from the computing device; a rendering system (4331) configured to display information indicating routes of the computing device; and a controller (4320) configured to: tracking the locations of the computing device (100) by determining that a location of the computing device (100) has changed based on the location information of the computing device (100) obtained by the location finder (4311), obtaining information corresponding to an initial route of the computing device (100) based on the tracked locations of the computing device (100), determining a predicted path of the computing device (100) based on the information corresponding to the initial path of the computing device (100) and the past location information of the computing device (100), display the expected path in the rendering system (4331) and controlling the location finder (4311) to track an actual location of the computing device (100) by varying a time interval of obtaining the location information of the computing device (100) based on at least one of the surrounding environment information of the computing device (100) and the intended route. 2. The computing device (100) of claim 1, wherein after displaying the intended path in the rendering system (4331), the controller (4320) is further configured to: updating the past location information of the computing device (100) based on the tracked locations of the computing device (100). The computing device (100) of claim 1, wherein the controller (4320) is further configured to control the location finder (4311) to obtain the initial route by varying a time interval of obtaining the location information of the computing device (100) based on at least one of a movement speed of the computing device (100) and the information of the surrounding environment of the computing device (100). The computing device (100) of claim 1, wherein if the intended route is not determined from the past location information of the computing device (100) based on the initial route, the controller (4320) is configured furthermore to control the location finder to track the actual location of the computing device (100) by varying a time interval of obtaining the location information of the computing device (100) based on at least one of a movement speed and information of the surrounding environment of the computing device (100), and updating the past location information of the computing device (100) based on the tracked locations of the computing device (100). The computing device (100) of claim 1, wherein the controller (4320) is further configured to display personalized information about the computing device (100) in the rendering system (4331) based on the intended path of the device (100) computer and the profile information of a user of the computer device (100). The computing device (100) of claim 5, wherein the controller (4320) is further configured to display recommendation information in the rendering system (4331) including at least one article of recommended content based on information from profile of a place adjacent to the intended route and user profile information, in which the recommended content includes a topic article, in which the controller (4320) is further configured to provide the recommended content in the form of a map or a notification, in which the controller (4320) is further configured to detect regional information about a region adjacent to the intended route, in which the regional information includes information about where a group of people is currently active, and shows the regional information detected in the representation system (4331). The computing device of claim 5, wherein the controller (4320) is further configured to detect a usage count of the computing device (100) on the predicted route from the past location information of the device (100) computer, and display in the representation system (4331) the personalized information according to the detected usage count. 8. A procedure for providing personalized information, performed by a computing device (100), comprising the procedure: obtaining information about an initial path of the computing device (100) by tracking locations of the computing device (100) determining that a location of the computing device (100) has changed; determining a predicted path of the computing device (100) based on the information corresponding to the initial path of the computing device (100) and past location information of the computing device (100); displaying the intended route in a computer device (100) representation system (4331); and tracking an actual location of the computing device by varying a time interval for obtaining location information from the computing device (100) based on at least one of the information from the surrounding environment of the computing device (100) and the predicted route. The method of claim 8, further comprising, after displaying the intended route in the rendering system (4331), updating the past location information of the computing device (100) based on the tracked locations of the computing device (100). The method of claim 8, wherein obtaining information about the initial route of the computing device (100) comprises obtaining information about the initial route of the computing device (100) while varying a time interval of obtaining the information. location information of the computing device (100) based on at least one between a movement speed of the computing device (100) and the information of the surrounding environment of the computing device (100). The method of claim 8, wherein, if the intended route is not determined from the past location information of the computing device (100) based on the initial route of the computing device (100), the method comprises : tracking the actual location of the computing device (100) by varying a time interval of obtaining location information of the computing device (100) based on at least one of a speed of movement of the computing device (100) and the information of the surrounding environment of the computer device (100); and updating the past location information of the computing device (100) based on the tracked locations of the computing device (100). The method of claim 8, further comprising providing personalized information about the computing device (100) based on the intended path of the computing device (100) and profile information of a user of the computing device (100). The method of claim 12, wherein providing personalized information about the computing device (100) further comprises providing recommendation information including at least one article of recommended content based on profile information from a location adjacent to the expected route and user profile information, in which the recommended content includes a topic article, wherein the procedure further comprises providing the recommended content in the form of a map or notification. 14. The method of claim 12, wherein providing personalized information about the computing device (100) further comprises: detect regional information about a region adjacent to the intended route in which regional information includes information about where a group of people is currently active; and provide the detected regional information. The method of claim 12, further comprising detecting a usage count of the computing device (100) on the predicted route from the past location information of the computing device (100), and providing the personalized information based on the count of detected use.