WO2019059435A1

WO2019059435A1 - Method and system for making recommendations using content including location data

Info

Publication number: WO2019059435A1
Application number: PCT/KR2017/010511
Authority: WO
Inventors: 홍석주
Original assignee: 라인 가부시키가이샤
Priority date: 2017-09-22
Filing date: 2017-09-22
Publication date: 2019-03-28
Also published as: KR102489339B1; JP7345020B2; JP2022133400A; JP7102513B2; KR20220026609A; JP2021503111A; KR102365967B1; KR20200014416A

Abstract

Disclosed is a recommendation technology using content including location data. A method for providing recommendation information comprises the steps of: collecting photographs which are uploaded on an online community and include location data; constructing location-based recommendation information by grouping the collected photographs by using the location data; and providing a map screen including a location specified by a user of an electronic device when a request for a location-based recommendation service is received through the online community from the electronic device and providing the photographs that have been grouped with respect to the location data in a corresponding map through the map screen.

Description

Recommendation method and system using contents containing position data

The description below relates to a technique for providing location based services.

As the infrastructure for location-based content creation, for example, smartphones or global positioning systems (GPS), becomes popular, the use of location-based services is increasing rapidly.

The types of content available to users through location-based services also vary from photographs, music, videos, games, real-time information content, and so on.

An example of a technology for providing a location-based service is disclosed in Korean Patent Registration No. 10-1556559 (registered on September 23, 2015), which provides merchant information based on location information of the current user to the user terminal in real time , Information on a discount or mileage use provided by the franchisee for attracting customers, and information on the franchisee where the number of current customers is low is provided to the user terminal.

A method and system for providing location-based recommendation information using content including location data among contents uploaded through an Internet community for communication among users.

And provides a method and system for recommending actual uploaded contents by people having a predetermined relationship with a user in the Internet community through a map of a location specified by a user.

A computer-implemented recommendation information providing method, comprising: collecting photographs uploaded through an Internet community and including position data; Constructing location-based recommendation information by grouping the collected photographs using the location data; And providing a map screen including a location specified by a user of the electronic device when a request for a location based recommendation service is received from the electronic device through the Internet community, The recommendation information providing method comprising the steps of:

According to an aspect of the present invention, the collecting may include storing a position ID assigned to an area corresponding to the position data of the collected photograph with respect to the collected photograph.

According to another aspect, the constructing step may include classifying the collected photographs into a group of photographs for a position ID assigned to an area corresponding to the position data of the collected photographs.

According to another aspect of the present invention, a location ID is allocated to each divided area of a map, and the configuring step comprises: a step of configuring a photo group by the location ID, And grouping the photos including the location data of the area allocated with the location ID into the photo group by location ID.

According to another aspect, the configuring step may include the step of re-grouping the photo groups by location ID into a plurality of categories according to the contents of the photos belonging to the photo group through image analysis.

According to another aspect, the configuring step may include re-grouping the photo groups for each location ID into a plurality of categories using the attribute information or the tag information included in the photos belonging to the photo group.

According to another aspect of the present invention, the providing step may include a step of providing the location-based recommendation service based on the identification information of the Internet community requested by the user and the social network information of the user in the Internet community, And at least a part of the at least a part of the at least one of the plurality of images.

According to another aspect, the providing step may include: when the user requests the location-based recommendation service through a specific chat room of the Internet community, among the photos grouped on location data in the map, And selectively providing the uploaded photographs.

According to another aspect of the present invention, the providing step may include: when the user requests the location-based recommendation service without specifying a conversation partner through the Internet community, And providing a photo uploaded by at least one other user associated with the user in accordance with the user's social network information in the user.

According to another aspect of the present invention, there is provided a recommendation information providing method, wherein when there are a plurality of picture groups for each location ID on the map screen, the number of pictures of each picture group, the number of views, Calculating a recommendation score based on at least one element among the plurality of position IDs, the latestness according to time, and the proximity to a position specified by the user, wherein the providing step comprises: And reflecting the ranking according to the recommendation score.

According to another aspect of the present invention, the calculating step calculates a weighting factor for each of at least two elements among the number of pictures of each picture group, the number of views, the latestness according to the uploading time of the picture, And calculating a recommendation score for each group of pictures.

According to another aspect of the present invention, the configuring step includes a step of re-grouping the photo groups for each location ID into a plurality of categories using a photo belonging to the photo group, wherein the recommendation information providing method includes: Calculating a category score based on at least one element among the number of pictures of the photograph group for each category, the number of views, the latest property according to the photo upload time, and the proximity to the position specified by the user, The providing step may include providing category groups of photo groups for the plurality of categories, reflecting the ranking according to the category scores.

And a computer program stored in a computer-readable recording medium for causing the computer to execute the recommendation information providing method in combination with the computer.

There is provided a computer-readable recording medium having recorded thereon a program for causing a computer to execute the recommendation information providing method.

A computer-implemented recommendation information providing system, comprising: at least one processor; And a memory coupled to the at least one processor and including instructions executable by the at least one processor, the at least one processor collecting photos uploaded via the Internet community and containing location data Based recommendation information by grouping the collected photographs using the location data, and when a request for a location-based recommendation service is received from the electronic device through the Internet community, Wherein the recommendation information providing system operates when an instruction is provided to provide a map screen including a location, and to provide pictures grouped with location data in the map through the map screen.

According to embodiments of the present invention, it is possible to effectively provide location-based recommendation information using content including location data, among contents uploaded through an Internet community for communication between users.

According to embodiments of the present invention, it is possible to recommend contents uploaded by people who have a predetermined relationship with the user in the Internet community through a map of a location specified by the user.

1 is a diagram illustrating an example of a network environment according to an embodiment of the present invention.

2 is a block diagram for explaining an internal configuration of an electronic device and a server in an embodiment of the present invention.

3 is a diagram illustrating an example of a location based recommendation service environment in an embodiment of the present invention.

4 is a diagram illustrating an example of a component that a processor of a server according to an embodiment of the present invention may include.

5 is a flowchart illustrating an example of a method that a server according to an embodiment of the present invention can perform.

6 is an exemplary diagram for explaining a process of assigning a location ID to a photograph in an embodiment of the present invention.

FIG. 7 is an exemplary diagram for explaining a process of sorting photographs including position data in an embodiment of the present invention.

8 to 9 illustrate examples of screens that can request a location-based recommendation service according to an exemplary embodiment of the present invention.

FIGS. 10 to 11 illustrate screen examples for providing location-based recommendation information in an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Embodiments of the present invention relate to a technique for providing location-based services, and more particularly, to a method and system for providing location-based recommendation information using content including location data.

Embodiments including those specifically disclosed herein can provide location-based recommendation information using content that includes location data and provide significant advantages in terms of efficiency, effectiveness, convenience, and cost savings .

1 is a diagram illustrating an example of a network environment according to an embodiment of the present invention. 1 shows an example in which a plurality of

electronic devices

110, 120, 130, 140, a plurality of

servers

150, 160, and a network 170 are included. 1, the number of electronic devices and the number of servers are not limited to those shown in FIG.

The plurality of

electronic devices

110, 120, 130, 140 may be a fixed terminal implemented as a computer device or a mobile terminal. A mobile phone, a tablet PC, a navigation device, a computer, a notebook, a digital broadcasting terminal, a PDA (personal digital assistant), a PMP (personal digital assistant) Portable Multimedia Player). For example, the first electronic device 110 may communicate with other

electronic devices

120, 130, 140 and / or the

servers

150, 160 via the network 170 using a wireless or wired communication scheme.

The communication method is not limited, and may include a communication method using a communication network (for example, a mobile communication network, a wired Internet, a wireless Internet, a broadcasting network) that the network 170 may include, as well as a short-range wireless communication between the devices. For example, the network 170 may be a personal area network (LAN), a local area network (LAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN) , A network such as the Internet, and the like. The network 170 may also include any one or more of a network topology including a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree or a hierarchical network, It is not limited.

Each of the

servers

150 and 160 is a computer device or a plurality of computers that communicate with a plurality of

electronic devices

110, 120, 130 and 140 through a network 170 to provide commands, codes, files, Lt; / RTI > devices. For example, the server 160 may provide a file for installation of an application to the first electronic device 110 connected via the network 170. [ In this case, the first electronic device 110 can install an application using a file provided from the server 160. [ The server 150 is connected to the server 150 according to the control of an operating system (OS) included in the first electronic device 110 or at least one program (for example, a browser or an installed application) Services and contents can be provided. For example, if the first electronic device 110 transmits a service request message to the server 150 via the network 170 under the control of the application, the server 150 transmits a code corresponding to the service request message to the first And the first electronic device 110 can provide contents to the user by displaying and displaying a screen according to the code according to the control of the application.

2 is a block diagram for explaining an internal configuration of an electronic device and a server in an embodiment of the present invention. In FIG. 2, the internal configuration of the first electronic device 110 as an example of one electronic device and the server 150 as an example of one server will be described. Other

electronic devices

120, 130, 140 or server 160 may have the same or similar internal configurations.

The first electronic device 110 and the server 150 may include

memories

211 and 221,

processors

212 and 222,

communication modules

213 and 223 and input /

output interfaces

214 and 224. The

memories

211 and 221 may be a computer-readable recording medium and may include a permanent mass storage device such as a random access memory (RAM), a read only memory (ROM), and a disk drive. The

memory

211 and 221 may store an operating system or at least one program code (for example, codes for an application installed and driven in the first electronic device 110). These software components may be loaded from a computer readable recording medium separate from the

memories

211 and 221. [ Such a computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, and a memory card. In other embodiments, the software components may be loaded into

memory

211, 221 via

communication modules

213, 223 rather than a computer readable recording medium. For example, at least one program may be a program installed by a file distribution system (for example, the server 160 described above) that distributes installation files of developers or applications, May be loaded into the

memory

211, 221 based on the application described above.

Processors

212 and 222 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input / output operations. The instructions may be provided to the

processors

212 and 222 by the

memories

211 and 221 or the

communication modules

213 and 223. For example, the

processors

212 and 222 may be configured to execute instructions received in accordance with program codes stored in a recording device, such as

memories

211 and 221. [

The

communication modules

213 and 223 may provide a function for the first electronic device 110 and the server 150 to communicate with each other through the network 170 and may be connected to other electronic devices ) Or another server (e.g., server 160). For example, a request (e.g., a search request) generated by the processor 212 of the first electronic device 110 in accordance with a program code stored in a recording device, such as the memory 211, To the server 150 via the Internet 170. Conversely, control signals, commands, contents, files, and the like provided under the control of the processor 222 of the server 150 are transmitted to the communication module 223 of the first electronic device 110 via the communication module 223 and the network 170, May be received by the first electronic device (110) via the second network (213). For example, the control signal or command of the server 150 received through the communication module 213 may be transmitted to the processor 212 or the memory 211, and contents or files may be transmitted to the first electronic device 110, May also be stored as a storage medium.

The input / output interface 214 may be a means for interfacing with the input / output device 215. For example, the input device may include a device such as a keyboard or a mouse, and the output device may include a device such as a display for displaying a communication session of the application. As another example, the input / output interface 214 may be a means for interfacing with a device having integrated functions for input and output, such as a touch screen. The processor 212 of the first electronic device 110 may use the data provided by the server 150 or the second electronic device 120 in processing the instructions of the computer program loaded into the memory 211. For example, A service screen or contents configured by the user can be displayed on the display through the input / output interface 214. [ The input / output interface 224 can also output information configured using the data provided by the server 150 in processing the instructions of the computer program loaded in the memory 221 by the processor 222 of the server 150 have.

Also, in other embodiments, the first electronic device 110 and the server 150 may include more components than the components of FIG. However, there is no need to clearly illustrate most prior art components. For example, the first electronic device 110 may be implemented to include at least some of the input / output devices 215 described above, or may be implemented as a transceiver, a Global Positioning System (GPS) module, a camera, And may further include components. More specifically, when the first electronic device 110 is a smart phone, it may be an acceleration sensor, a gyro sensor, a camera, various physical buttons, buttons using a touch panel, input / output ports, It is understood that various components such as a vibrator may be further included in the first electronic device 110.

Hereinafter, a method and system for providing location-based recommendation information using content including location data will be described.

The recommendation information providing system implemented by a computer may be configured in the server 150 according to the present embodiment. The server 150 provides a location-based recommendation service for a plurality of

electronic devices

110, 120, 130 and 140 as a client. The server 150 provides location-based recommendation services on the

electronic devices

110, 120, 130 and 140 It is possible to provide recommendation information corresponding to a service request through access to a web / mobile site associated with a dedicated application or server 150 installed.

Referring to FIG. 3, the server 150 may serve as a recommendation server for providing a location-based recommendation service, and may be implemented as a service platform with a community server providing a community service, or as a separate service platform Based recommendation service can be provided through linkage with the community service in cooperation with the community server.

In this specification, the community may include all communication means on the Internet for communication between users, and may include, for example, a messenger or a social network service (SNS).

When the user transmits the content including the location data as a message or registers in the SNS, the content may be delivered to the destination (another user or the SNS) after the location data is removed. At this time, the server 150 may construct the location-based recommendation information using the content including the location data as content to be uploaded through the Internet community, and may provide the location-based recommendation service to the user requesting the location-based recommendation service.

In this specification, the content may include all information provided through the Internet, and may include, for example, a photograph or an image, a moving image, a voice, a document, music, and the like. In the following specific embodiments, photographs are described as typical examples of contents, but the present invention is not limited thereto.

FIG. 4 is a diagram illustrating an example of a component that a server of a server according to an embodiment of the present invention can include; FIG. 5 is a diagram illustrating an example of a method that a server can perform according to an exemplary embodiment of the present invention; Fig.

4, the server 150 of the server 150 includes a collecting unit 410, an information constructing unit 420 (refer to FIG. 4) A ranking calculating unit 430, and an information providing unit 440. [ The components of processor 222 may optionally be included or excluded from processor 222 in accordance with an embodiment. In addition, in accordance with an embodiment, the components of the processor 222 may be separate or merged for the representation of the functionality of the processor 222.

The components of the processor 222 and the processor 222 may control the server 150 to perform the steps S510 to S540 included in the recommendation information providing method of FIG. For example, the components of processor 222 and processor 222 may be implemented to execute instructions in accordance with the code of the operating system and the code of at least one program that memory 221 contains.

Herein, the components of processor 222 may be representations of different functions of processor 222 performed by processor 222 in accordance with instructions provided by the program code stored in server 150 . For example, the collection unit 410 may be used as a functional representation of the processor 222 that controls the server 150 in accordance with the above-described command so that the server 150 collects the content containing the location data.

In step S510, the processor 222 can read the necessary commands from the loaded memory 221 with instructions related to the control of the server 150. [ In this case, the read command may include instructions for controlling the processor 222 to execute the steps (S520 to S540) to be described later.

In step S520, the collecting unit 410 may collect photographs including position data among the photographs uploaded from the plurality of

electronic devices

110, 120, 130, The collection unit 410 can collect the corresponding photographs as contents available in the location-based recommendation service when users upload and take pictures including location data in an Internet community for communication between users, for example, a messenger or a SNS. The user who has accepted the location sharing in advance can receive the location data of the

electronic devices

110, 120, 130 and 140 together with the photograph in the photo uploading process and store it on the database associated with the server 150 So that a photograph including position data can be collected. In this case, the position data stored in the database may be a specific position value such as the GPS coordinates of the

electronic devices

110, 120, 130, 140, and in another example, And may be a location ID. In detail, a method of dividing the entire map into a plurality of regions and assigning a unique position ID to each of the divided regions may be utilized. At this time, the collecting unit 410 may collect a photograph including position data, Rather than storing a specific position value acquired from the electronic device, the position ID corresponding to the position value is stored as estimated position information. In addition, the position data may be a position value automatically obtained through the GPS or the like in the electronic device, or may be position information directly input by the user. The collection unit 410 may store the identification information (e.g., userID) of the user who uploaded the photograph as the information related to the photograph in the process of collecting the photograph including the location data together with the community identification information. At this time, the community identification information is information about the community to which the user has transmitted the picture, for example, in the case of the messenger (individual or group), the chat room ID or the like corresponds to the community identification information, Information.

In step S530, the information constructing unit 420 may construct the location-based recommendation information using the photographs including the location data collected on the database. For example, the information constructing unit 420 may group the collected photographs using position data. The information constructing unit 420 may group photos according to the location IDs, and may store the location IDs for the location IDs or group the photos storing the location values of the areas belonging to the location IDs. Then, the information constructing unit 420 may group the collected photographs into a plurality of categories according to the content of the photograph through an image analysis technique using artificial intelligence (AI) or the like. In addition to the image analysis technique, it is also possible to classify photographs into various categories using attribute information included in the photographs or tags directly input by the user (for example, food menu names are input for food photographs). For example, a photograph can be classified into a background photograph and a food photograph, and a food photograph can be subdivided by each menu. Categories for photo grouping can be predetermined according to service type or characteristics, and can be divided into various themes such as eating distance, sightseeing, entertainment, and the like. Accordingly, the information constructing unit 420 can preferentially group the photographs including the position data by position IDs, further group the photographs into various categories through image analysis, and have similarity within a certain range within each category The same pictures can be re-grouped. In this manner, the information constructing unit 420 may configure the location-based recommendation information by grouping the collected photographs based on the location ID and / or the image analysis result. The information constructing unit 420 groups the collected photographs into a group of photos by location ID based on the location ID and re-groups the groups of photos by location ID into a plurality of categories based on the image analysis result, .

In step S540, when the request for the location-based recommendation service is received from the user of the first electronic device 110, the information providing unit 440 corresponds to the corresponding map through the map screen including the location specified by the user Based recommendation information. The location specified by the user may refer to the current location of the user obtained from the first electronic device 110 or a location directly selected by the user. When the service request of the user is received, the information providing unit 440 can identify the location specified by the user at the time of receiving the service request and provide a map screen centered on the location, and at this time, And may provide photos grouped by location IDs in the map as location-based recommendation information. The service request of the user may include information on the category selected by the user. At this time, the information providing unit 440 may select only the pictures classified in the category selected by the user from among the pictures grouped by the location ID in the map . When the user requests the location-based recommendation service from the specific community, the information provider 440 grasps the identification information of the community requesting the location-based recommendation service by the user and the user's social network information in the community, Based on the photos uploaded by the people belonging to the community among the photos grouped by the location ID, as location-based recommendation information. For example, when a user requests a location-based recommendation service from a specific group chat room of a messenger, only a photo uploaded by people participating in the group chat room can be recommended. When a user requests a location-based recommendation service from a specific SNS, (E.g., a friend, a colleague, a family member, etc.) who is associated with the user. The information providing unit 440 provides pictures grouped for each location ID within a certain distance on the basis of the location on the map screen of the location specified by the user, (Other users related to the user who has requested the service according to the social network information) can be selected and recommended.

When providing a plurality of groups of pictures as location-based recommendation information (for example, when a group of pictures by a plurality of location IDs exists on a map screen including a location specified by a user, (E.g., when there are a plurality of groups of pictures of different categories for the ID), ranking based on the recommendation score may be reflected. At this time, the ranking calculation unit 430 calculates a recommendation score or a category score for each group of pictures with respect to a location ID or a category (which is classified using photographs, such as an image analysis result of a photograph) A weight can be given to at least one of the number of pictures, the number of views, the latestness (time), and the proximity (position) of each group. For the group of pictures, the more the number of photos uploaded by the users, the higher the number of views of the photos, the more recently uploaded photos (the shorter the elapsed time after uploading), and / A higher recommendation score or category score can be calculated as the location is closer to a specified location. Since the number of views and the latestness among the above factors may be different for each of the pictures belonging to the group, the number of views of the picture group is a value obtained by averaging the number of views of the pictures included in the group, or by using the highest number of views of the pictures included in the group And the latestness of the group of pictures can be determined by using the upload time of the most recently uploaded picture among the pictures included in the group. In this case, not only a certain weight is given to all the elements, but it is also possible that the weight is applied differently depending on the elements. For example, weights of 40%, 30%, 20%, 10%, or 20, 10, 10, and 1 can be applied to the number of pictures, views, Element can be given a lower weight. As another example, weights can be applied differently depending on the type and characteristics of the categories that are used to classify the photographs. For example, in case of food photographs, weights of the highest specific gravity can be given to the latest one, and in the case of background photographs, the weight of the highest specific gravity can be given to the number of photographs. Accordingly, the information providing unit 440 provides location group recommendation information for each group of the location IDs within a certain distance based on the location on the map screen of the location specified by the user, and the ranking calculator 430 The group of photographs can be provided in the order of recommendation score reflecting the calculated ranking. The information providing unit 440 may further include a step of, when the group of photo IDs by location ID is re-grouped into a plurality of categories, the grouping of photo groups by category with respect to a plurality of categories, Can be provided.

When the user of the first electronic device 110 uploads a photograph including location data through a community such as a messenger or the SNS, the collecting unit 410 stores the photograph including the location data as content usable in the location-based recommendation service Collect. As shown in FIG. 6, it is assumed that the entire map 600 is divided into a plurality of areas of a predetermined size, and a position ID is assigned to each of the divided areas. At this time, when the photograph includes the GPS coordinates value 601 indicating the exact position of the first electronic device 110, the collecting unit 410 does not store the GPS coordinate value 601, May store the location ID assigned to the area 610 to which the value 601 belongs.

In the process of collecting the photographs, the GPS coordinate values 601 included in the photographs are stored as they are, and then the photographs including the GPS coordinate values 601 in the grouping process of the information composing unit 420 It is also possible to classify the GPS coordinate value 601 into a photograph group for the position ID of the area 610 to which the GPS coordinate value 601 belongs.

The information constructing unit 420 may configure the location-based recommendation information by grouping the collected photographs based on the location ID and the image analysis result. Referring to FIG. 7, the information constructing unit 420 may group the photographs collected on the database 151 based on the position ID first (e.g., position 1 group, position 2 group,?). Then, the information constructing unit 420 may re-group the photo groups by location ID into the subcategories by using the photos belonging to the respective photo groups. At this time, the re-grouping means to subdivide the pictures classified by the position ID into one or more category depths and classify them into the first level category, the second level category, and? According to the depth. For example, the information constructing unit 420 may analyze each of the images of the photographs belonging to the position 1 group (position ID = 'position 1') to generate a group of background pictures (first level category = 'background' (First level category = 'food'), and the food photograph group can be subdivided by each menu to regroup (for example, menu 1 group (second level category = 'menu 1'), menu 2 groups (second level category = 'menu 2'), etc.).

Accordingly, the information constructing unit 420 can group the photographs including the position data basically by the position IDs and group them into the photograph group by the position IDs. In the group by the position IDs, You can re-group into categories.

8 shows a chat screen 800 of a messenger that is one of the Internet communities. The chat room screen 800 is a user interface screen in which a user can exchange a chat with a message or send and receive various contents such as a photo, a moving image, and a voice. In addition to an individual chat room having one chat partner, Group chat room. As shown in FIG. 8, the chat room screen 800 may include a recommendation menu 801 for requesting a location-based recommendation service by a user.

9 shows a chat room list screen 900 of the messenger. As shown in FIG. 9, the chat room list screen 900 may include a chat room list 910 in which a user arranges chat rooms for exchanging messages and contents with each other. For example, the chat room list 910 may be sorted in descending order based on the time of sending and receiving messages, which is one of the existing sorting criteria. In other words, the chat room may be sorted on the list have. At this time, the chat room list screen 900 may include a recommendation menu 901 for requesting a location based recommendation service by the user.

The chat room screen 800 or the chat room list screen 900 may further include a menu that allows the user to select a category of information to be recommended.

8 and 9 are illustrative and not intended to limit the present invention. However, the present invention is also applicable to a location-based recommendation service through a friend list screen including a friend list of a messenger or a user interface screen of a community such as an SNS You can provide a menu to access.

When the user operates the

recommendation menus

801 and 901 on the chatting screen 800 or the chatting room list screen 900, a map screen 1011 (Fig. 10) centered on the position 1011 specified by the user 1000) may be displayed. The map screen 1000 includes a map indicating the current position of the user or a position selected by the user. The recommendation information 1020 based on the location 1011 specified by the user can be exposed on the map screen 1000 and the recommended information 1020 can be displayed on the map screen 1000 for every location ID Recommendation information 1020 may be displayed. For example, the recommendation information 1020 may include at least one of representative photograph (s) arbitrarily selected in the group and the number of pictures 1021 classified into the group, as information on the photo group.

If the user requests the location-based recommendation service through the chat room screen 800 in which the chat party is specified, only the photo uploaded by the party participating in the chat room can be provided as the recommendation information 1020, Based recommendation service is requested from a screen (for example, a chat room list screen 900 or a friend list screen (not shown)) or a community screen, all the people (entire friends) having a predetermined relationship with the user in the community are uploaded The recommendation information 1020 can be provided.

If there are two or more picture groups per location ID included in the map screen 1000, the ranking according to the recommendation score for the picture group by location ID is reflected and can be provided as recommendation information 1020. At this time, the recommendation score can be calculated by weighting at least one element among the number of pictures, the number of views, the latestness (time), and the proximity (position) of each picture group. For example, in the map screen 1000, the recommendation score is higher or the number of views is larger, the recommendation information 1020 for a group of photos by location ID can be displayed larger.

If the group of photos by location ID is reclassified into categories, recommendation information 1020 can be displayed for each category on the map screen 1000. When the category is selected at the time of the service request of the user, only the pictures classified into the category selected by the user among the pictures grouped by the location ID in the map screen 1000 can be provided as the recommendation information 1020.

11, when a user selects recommendation information 1020 of a specific location ID on the map screen 1000, a detailed service screen 1100 including a photo list 1110 grouped in the location ID may be displayed . For example, when the user selects the 'food' category, a photo list 1110 classified as 'food' may be displayed in the detailed service screen 1100 of the group of photos of the corresponding location ID. At this time, the picture list 1110 is made up of pictures belonging to the category 'food'. At this time, the picture list 1110 can be grouped according to a detailed category, for example, a menu (menu 1, menu 2, menu 3).

In the photograph list 1110, rankings according to the category scores may be reflected on the photograph groups of the detailed categories. At this time, the recommendation score can be calculated by weighting at least one of the number of pictures, the number of views, the latestness (time), and the proximity (position) of each picture group. For example, The category scores of the photo group can be displayed in sorted order.

Accordingly, the user can confirm whether a place is popular with the person in the community or the party in the chat room through the current position or the map screen of the directly selected place in the environment using the community such as messenger or SNS, Is popular.

Although a photograph has been described above, the present invention can be applied to any type of content that can be provided as location-based recommendation information.

According to embodiments of the present invention, location-based recommendation information can be effectively provided using content including location data, among contents uploaded through an Internet community for communication between users. In particular, according to embodiments of the present invention, it is possible to recommend contents uploaded by persons who have a predetermined relationship with a user in the Internet community through a map of a location specified by a user.

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented as a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit, a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be embodied in any type of machine, component, physical device, computer storage media, or device for interpretation by a processing device or to provide instructions or data to the processing device have. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. At this time, the medium may be a program that continuously stores a computer executable program, or temporarily stores the program for execution or downloading. Further, the medium may be a variety of recording means or storage means in the form of a combination of a single hardware or a plurality of hardware, but is not limited to a medium directly connected to any computer system, but may be dispersed on a network. Examples of the medium include a magnetic medium such as a hard disk, a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floptical disk, And program instructions including ROM, RAM, flash memory, and the like. As another example of the medium, a recording medium or a storage medium that is managed by a site or a server that supplies or distributes an application store or various other software is also enumerated.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims

A recommendation information providing method implemented by a computer,

Collecting photos uploaded via an Internet community and including location data;

Constructing location-based recommendation information by grouping the collected photographs using the location data; And

Based recommendation service is received from the electronic device through the Internet community, a map screen including a location specified by a user of the electronic device is provided, Steps to provide photos

Based on the recommendation information.
The method according to claim 1,

Wherein the collecting comprises:

And storing a location ID assigned to an area corresponding to the collected location data of the collected photographs.
The method according to claim 1,

Wherein the configuring comprises:

And classifying the collected photographs into a group of photographs for a position ID assigned to an area corresponding to the position data of the collected photographs.
The method according to claim 1,

Each segmented area of the map is assigned a location ID,

Wherein the configuring comprises:

Grouping the photos including the location IDs into the photo IDs of the location IDs and the photos containing the location data of the areas having the location IDs by the location IDs, , Recommendation information providing method.
5. The method of claim 4,

Wherein the configuring comprises:

And grouping the group of photo IDs by location ID into a plurality of categories according to the content of the photographs belonging to the group of photographs through image analysis.
5. The method of claim 4,

Wherein the configuring comprises:

And grouping the group of photo IDs by location ID into a plurality of categories using attribution information or tag information included in the photographs belonging to the photo group.
The method according to claim 1,

Wherein the providing step comprises:

Selecting and providing at least some of the photos grouped into the location data based on the identification information of the Internet community requesting the location based recommendation service and the user's social network information in the Internet community, , Recommendation information providing method.
8. The method of claim 7,

Wherein the providing step comprises:

If the user requests the location-based recommendation service through a specific chat room of the Internet community, selecting and providing the photos uploaded by the people participating in the chat room among the photos grouped on the location data in the map , Recommendation information providing method.
8. The method of claim 7,

Wherein the providing step comprises:

If the user requests the location-based recommendation service without specifying a conversation partner through the Internet community, the user can select the location-based recommendation service based on the user's social network information in the Internet community, And providing a photo uploaded by at least one other user associated with the recommendation information.
The method according to claim 5 or 6,

The recommendation information providing method includes:

Wherein, if there are a plurality of photo groups for each location ID, the number of photographs of each photo group, the number of views, the latest property according to the photo upload time, the location specified by the user And adjacency with the reference score, wherein the recommendation score is calculated based on at least one of the following:

Wherein the providing step comprises:

And providing the plurality of group of photo IDs by location ID reflecting the ranking according to the recommendation score.
11. The method of claim 10,

Wherein the calculating step comprises:

A recommendation score for each picture group is calculated by assigning weights to at least two or more elements among the number of pictures of each picture group, the number of views, the latestness according to the upload time of the picture, and the proximity to the location specified by the user The recommendation information providing method comprising the steps of:
11. The method of claim 10,

Wherein the configuring comprises:

Grouping the photo groups by location ID into a plurality of categories using the photos belonging to the photo group,

The recommendation information providing method includes:

Calculating a category score based on at least one element among the number of pictures of the photograph group for each category, the number of views, the latestness according to the uploading time of the photograph, and the proximity to the position specified by the user for the plurality of categories, Including,

Wherein the providing step comprises:

And providing the group of photographs for each of the plurality of categories by reflecting the ranking according to the category score.
A computer program stored in a computer-readable medium for causing a computer to execute the method for providing recommended information according to any one of claims 1 to 9 in combination with a computer.
A computer-readable recording medium storing a program for causing a computer to execute the recommendation information providing method according to any one of claims 1 to 9.
A recommendation information providing system implemented by a computer,

At least one processor; And

A memory coupled to the at least one processor and including instructions executable by the at least one processor,

Lt; / RTI >

Wherein the at least one processor comprises:

Collect photos that are uploaded via the Internet community and contain location data,

Based recommendation information by grouping the collected photographs using the position data,

Based recommendation service is received from the electronic device through the Internet community, a map screen including a location specified by a user of the electronic device is provided, Wherein the recommendation information providing system operates when executing an instruction to provide photographs.
16. The method of claim 15,

Each segmented area of the map is assigned a location ID,

To construct the location-based recommendation information,

And grouping the photos including the location IDs into the photo IDs of the location IDs and the photos containing the location data of the areas where the location IDs are allocated, Recommended information providing system.
17. The method of claim 16,

To construct the location-based recommendation information,

Grouping the group of photo IDs by location ID into a plurality of categories according to the content of the photographs belonging to the photo group through image analysis.
16. The method of claim 15,

Providing the grouped pictures may include:

Based recommendation service and the social network information of the user in the Internet community among the photos grouped on the location data in the map based on the identification information of the Internet community requesting the location- And selectively providing photos uploaded by at least one other user associated with the user in accordance with the social network information.
17. The method of claim 16,

Wherein the at least one processor comprises:

Wherein, if there are a plurality of photo groups for each location ID, the number of photographs of each photo group, the number of views, the latest property according to the photo upload time, the location specified by the user And the adjacency with < RTI ID = 0.0 > a < / RTI >

Providing the grouped pictures may include:

And providing the plurality of group of photo IDs by location ID reflecting the ranking according to the recommendation score.
20. The method of claim 19,

To construct the location-based recommendation information,

Grouping the photo groups by location ID into a plurality of categories using the photos belonging to the photo group,

Wherein the at least one processor comprises:

A command for calculating a category score based on at least one element among the number of pictures of each of the category photograph groups, the number of views, the latestness according to the photo upload time, and the proximity to the position specified by the user for the plurality of categories It also works when executed,

Providing the grouped pictures may include:

And providing the group of photographs for each of the plurality of categories by reflecting the ranking according to the category score.