KR102365967B1 - Recommendation method and system using content containing location data - Google Patents

Abstract

A recommendation technology using content including location data is disclosed. The method for providing recommended information includes collecting photos uploaded through an Internet community and including location data; configuring location-based recommendation information by grouping the collected photos using the location data; and when a request for a location-based recommendation service is received from an electronic device through the Internet community, providing a map screen including a location specified by a user of the electronic device, but grouping location data in the map through the map screen and providing the old photos.

Description

Recommendation method and system using content containing location data

The description below relates to technology for providing location-based services.

As an infrastructure for generating location-based content, for example, a smartphone or a global positioning system (GPS) becomes popular, the use of location-based services is rapidly increasing.

The types of content that users can use through location-based services are also diverse, such as photos, music, videos, games, and real-time information content, and the variety is gradually increasing.

As an example of a technology for providing a location-based service, Korean Patent Publication No. 10-1556559 (registration date September 23, 2015) provides affiliate information based on the location information of the current user to the user terminal in real time, or , a technology for providing information on discount or mileage use, etc. provided by a corresponding affiliate store to attract customers and information on affiliated stores with a low number of current users to a user terminal is disclosed.

A method and system for providing location-based recommendation information using content including location data among content uploaded through an Internet community for user-to-user communication are provided.

A method and system for recommending content actually uploaded by people who have a predetermined relationship with a user in an Internet community through a map of a location specified by a user are provided.

A computer-implemented method for providing recommended information, the method comprising: collecting photos uploaded through an Internet community and including location data; configuring location-based recommendation information by grouping the collected photos using the location data; and when a request for a location-based recommendation service is received from an electronic device through the Internet community, providing a map screen including a location specified by a user of the electronic device, but grouping location data in the map through the map screen It provides a method of providing recommended information, including the step of providing the photos.

According to one aspect, the collecting may include storing a location ID assigned to the area corresponding to the location data of the collected photos with respect to the collected photos.

According to another aspect, the configuring may include classifying the collected photos into photo groups for a location ID assigned to an area corresponding to the location data of the collected photos.

According to another aspect, a location ID is assigned to each divided area of the map, and the configuring includes: configuring a photo group for each location ID, a photo including the location ID for each location ID or a corresponding location ID The method may include grouping the photos including the location data in the allocated area into photo groups for each location ID.

According to another aspect, the configuring may include regrouping the photo group for each location ID into a plurality of categories according to content of photos belonging to the photo group through image analysis.

According to another aspect, the configuring may include regrouping the photo group by location ID into a plurality of categories using attribute information or tag information included in photos belonging to the photo group.

According to another aspect, in the providing, the photos grouped by the location data based on identification information of the Internet community in which the user has requested the location-based recommendation service and the user's social network information in the Internet community It may include the step of selecting and providing at least a portion of the.

According to another aspect, the providing may include, when the user requests the location-based recommendation service through a specific chat room of the Internet community, by people participating in the chat room among photos grouped for location data in the map. It may include selecting and providing the uploaded photos.

According to another aspect, in the providing step, when the user requests the location-based recommendation service without specifying a conversation partner through the Internet community, the Internet community among photos grouped with respect to the location data in the map and providing a photo uploaded by at least one other user related to the user according to the user's social network information in the .

According to another aspect, in the method for providing recommended information, when a plurality of photo groups by location ID exist on the map screen, the number of photos, the number of views, and uploading of photos of each photo group for the plurality of photo groups by location ID Comprising the step of calculating a recommendation score based on at least one factor of freshness over time and proximity to the location specified by the user, wherein the providing includes: It may include the step of reflecting and providing the ranking according to the recommendation score.

According to another aspect, the calculating may include weighting each of at least two or more factors among the number of photos in each photo group, the number of views, the freshness according to the upload time of the photos, and the proximity to the location specified by the user. and calculating a recommendation score for each photo group by giving the .

According to another aspect, the configuring includes regrouping the photo group by location ID into a plurality of categories using photos belonging to the photo group, and the method for providing recommended information includes: Comprising the step of calculating a category score based on at least one of the number of photos in the photo group for each category, the number of views, the freshness according to the photo upload time, and the proximity to the location specified by the user for each category, The providing may include providing photo groups for each category with respect to the plurality of categories by reflecting the ranking according to the category score.

It provides a computer program stored in a computer-readable recording medium in combination with a computer to cause the computer to execute the method for providing recommended information.

There is provided a computer-readable recording medium in which a program for executing the method for providing recommended information in a computer is recorded.

A computer-implemented recommendation information providing system, comprising: at least one processor; and a memory connected to the at least one processor and including instructions executable by the at least one processor, wherein the at least one processor collects photos uploaded through an Internet community and includes location data, , by grouping the collected photos using the location data to configure location-based recommendation information, and when a request for a location-based recommendation service is received from an electronic device through the Internet community, specified by the user of the electronic device Provided is a system for providing recommended information that provides a map screen including a location and operates when a command is executed to provide grouped photos for location data in a corresponding map through the map screen.

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

According to embodiments of the present invention, content actually uploaded by people having a predetermined relationship with the user in the Internet community may be recommended 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 the internal configuration of an electronic device and a server according to an embodiment of the present invention.
3 is a diagram illustrating an example of a location-based recommendation service environment according to an embodiment of the present invention.
4 is a diagram illustrating an example of components that a processor of a server may include according to an embodiment of the present invention.
5 is a flowchart illustrating an example of a method that a server may perform according to an embodiment of the present invention.
6 is an exemplary view for explaining a process of assigning a location ID to a photo according to an embodiment of the present invention.
7 is an exemplary diagram for explaining a process of classifying photos including location data according to an embodiment of the present invention.
8 to 9 are diagrams illustrating a screen for requesting a location-based recommendation service according to an embodiment of the present invention.
10 to 11 show examples of screens for providing location-based recommendation information according to an embodiment of the present invention.

Best mode for carrying out the invention

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 technology for providing a location-based service, and more particularly, to a method and system capable of providing location-based recommendation information using content including location data.

Embodiments including those specifically disclosed herein can provide location-based recommendation information using content including location data, which has significant advantages in terms of efficiency, effectiveness, convenience, cost reduction, etc. achieve them

1 is a diagram illustrating an example of a network environment according to an embodiment of the present invention. The network environment of FIG. 1 shows an example including a plurality of electronic devices 110 , 120 , 130 , 140 , a plurality of servers 150 , 160 , and a network 170 . 1 is an example for explaining the invention, and the number of electronic devices or the number of servers is not limited as in FIG. 1 .

The plurality of electronic devices 110 , 120 , 130 , and 140 may be a fixed terminal implemented as a computer device or a mobile terminal. Examples of the plurality of electronic devices 110 , 120 , 130 , 140 include a smart phone, a mobile phone, a tablet PC, a navigation device, a computer, a laptop computer, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Personal Digital Assistant) Portable Multimedia Player), etc. For example, the first electronic device 110 may communicate with other electronic devices 120 , 130 , 140 and/or the servers 150 and 160 through the network 170 using a wireless or wired communication method.

The communication method is not limited, and not only a communication method using a communication network (eg, a mobile communication network, a wired Internet, a wireless Internet, a broadcasting network) that the network 170 may include, but also short-range wireless communication between devices may be included. For example, the network 170 may include a personal area network (PAN), a local area network (LAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), and a broadband network (BBN). , the Internet, and the like. In addition, the network 170 may 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, etc. not limited

Each of the servers 150 and 160 communicates with the plurality of electronic devices 110 , 120 , 130 , 140 and the network 170 through a computer device or a plurality of computers that provides commands, codes, files, contents, services, etc. It can be implemented in devices. For example, the server 160 may provide a file for installing an application to the first electronic device 110 connected through the network 170 . In this case, the first electronic device 110 may install an application using a file provided from the server 160 . In addition, the server 150 is provided by accessing the server 150 under the control of an operating system (OS) or at least one program (eg, a browser or the installed application) included in the first electronic device 110 . services or contents can be provided. For example, when the first electronic device 110 transmits a service request message to the server 150 through the network 170 under the control of the application, the server 150 transmits a code corresponding to the service request message to the first The content may be transmitted to the electronic device 110 , and the first electronic device 110 may provide content to the user by composing and displaying a screen according to the code according to the control of the application.

2 is a block diagram for explaining the internal configuration of an electronic device and a server according to 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 the server 160 may also have the same or similar internal configuration.

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 are computer-readable recording media and may include random access memory (RAM), read only memory (ROM), and permanent mass storage devices such as disk drives. Also, an operating system or at least one program code (eg, a code for an application installed and driven in the first electronic device 110 ) may be stored in the memories 211 and 221 . These software components may be loaded from a computer-readable recording medium separate from the memories 211 and 221 . The separate 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 another embodiment, the software components may be loaded into the memories 211 and 221 through the communication modules 213 and 223 instead of a computer-readable recording medium. For example, the at least one program is a program installed by files provided through the network 170 by a file distribution system (eg, the above-described server 160 ) for distributing installation files of developers or applications (eg, a program that is installed) may be loaded into the memories 211 and 221 based on the above-described application).

The processors 212 and 222 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. Commands 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 received instructions according to program code stored in a recording device such as the 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 other electronic devices (eg, the second electronic device 120 ) )) or other servers (eg, server 160 ). For example, a request (eg, a search request) generated by the processor 212 of the first electronic device 110 according to a program code stored in a recording device such as the memory 211 may be transmitted to a network according to the control of the communication module 213 . It may be transmitted to the server 150 through 170 . Conversely, a control signal, command, content, file, etc. provided under the control of the processor 222 of the server 150 passes through the communication module 223 and the network 170 to the communication module of the first electronic device 110 . It may be received by the first electronic device 110 through 213 . For example, a 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 be stored as a storage medium that may further include

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 mouse, and the output device may include a device such as a display for displaying a communication session of an application. As another example, the input/output interface 214 may be a means for an interface with a device in which functions for input and output are integrated into one, such as a touch screen. As a more specific example, the processor 212 of the first electronic device 110 uses data provided by the server 150 or the second electronic device 120 in processing a command of a computer program loaded into the memory 211 . A service screen or content configured by doing this may be displayed on the display through the input/output interface 214 . The input/output interface 224 can also output information configured by using the data provided by the server 150 when the processor 222 of the server 150 processes the command of the computer program loaded in the memory 221 likewise. there is.

In addition, in other embodiments, the first electronic device 110 and the server 150 may include more components than those of FIG. 2 . However, there is no need to clearly show most of the prior art components. For example, the first electronic device 110 is implemented to include at least a portion of the above-described input/output device 215 or other such as a transceiver, a global positioning system (GPS) module, a camera, various sensors, and a database. It may further include components. As a more specific example, when the first electronic device 110 is a smartphone, an acceleration sensor or a gyro sensor, a camera, various physical buttons, a button using a touch panel, an input/output port, and vibration It can be seen that various components such as a vibrator may be implemented to be further included in the first electronic device 110 .

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

A computer-implemented recommendation information providing system may be configured in the server 150 according to the present embodiment. The server 150 provides a location-based recommendation service to a plurality of electronic devices 110 , 120 , 130 , and 140 that are clients, and provides a location-based recommendation service on the electronic devices 110 , 120 , 130 , 140 Recommendation information corresponding to a service request through a web/mobile site connection related to an installed dedicated application or server 150 may be provided.

Referring to FIG. 3 , the server 150 may serve as a recommendation server providing a location-based recommendation service, and may be implemented as a single service platform with a community server providing a community service, or as a separate service platform. In conjunction with the community server, it is possible to provide a location-based recommendation service through connection with the community service.

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

When a user transmits content including location data as a message or registers with SNS, the corresponding content may be delivered to a destination (other user or SNS) after the location data is removed. In this case, the server 150 may configure location-based recommendation information using content that includes location data as content uploaded through an Internet community, and may provide it to a user requesting a location-based recommendation service.

In this specification, content may encompass all information provided through the Internet, and may include, for example, photos, images, videos, voices, documents, and music. In the following specific embodiment, a picture will be described as a representative example of the content, but the present invention is not limited thereto.

4 is a diagram illustrating an example of components that a processor of a server according to an embodiment of the present invention may include, and FIG. 5 is a diagram illustrating an example of a method that the server according to an embodiment of the present invention may include. It is a flowchart shown.

In order for the server 150 to perform the method of providing recommended information according to FIG. 5 , the processor 222 of the server 150 is a component, as shown in FIG. 4 , a collection unit 410 and an information configuration unit 420 . ), a ranking calculating unit 430 , and an information providing unit 440 may be included. Depending on the embodiment, components of the processor 222 may be selectively included in or excluded from the processor 222 . In addition, according to an embodiment, the components of the processor 222 may be separated or combined to express the functions of the processor 222 .

The processor 222 and the components of the processor 222 may control the server 150 to perform the steps S510 to S540 included in the method for providing the recommendation information of FIG. 5 . For example, the processor 222 and components of the processor 222 may be implemented to execute instructions according to the code of the operating system included in the memory 221 and the code of at least one program.

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

In step S510 , the processor 222 may read a necessary command from the memory 221 in which the command related to the control of the server 150 is loaded. In this case, the read command may include a command for controlling the processor 222 to execute steps S520 to S540 to be described later.

In step S520 , the collection unit 410 may collect photos including location data among photos uploaded from the plurality of electronic devices 110 , 120 , 130 , and 140 . The collection unit 410 may collect the photo as content usable in the location-based recommendation service when users take and upload a photo including location data in an Internet community for user-to-user communication, for example, a messenger or SNS. In the case of a user who has accepted location sharing in advance, location data of the electronic devices 110 , 120 , 130 , 140 may be received along with a photo in the process of uploading the photo, and stored in a database associated with the server 150 . By doing so, it is possible to collect photos with location data. In this case, the location data stored in the database may be a specific location value such as GPS coordinates of the electronic devices 110 , 120 , 130 , and 140 . It may be a location ID (identity). In detail, a method of dividing the entire map into a plurality of areas and assigning a unique location ID to each divided area can be utilized, in which case the collection unit 410 is targeted to a user who uploads a photo containing location data. Rather than storing the specific location value obtained from the electronic device, the location ID corresponding to the location value is stored as approximate location information. In addition, the location data may be a location value automatically obtained through GPS or the like in the electronic device or location information directly input by a user. In addition, the collection unit 410 may store the identification information (eg, userID) of the user who uploaded the picture and community identification information together as information related to the picture in the process of collecting the picture including the location data. In this case, the community identification information is information about the community to which the user has sent a photo. For example, in the case of a messenger (individual or group) chat room ID corresponds to community identification information, and in the case of SNS, the corresponding community ID is community identification. information may be relevant.

In step S530 , the information configuration unit 420 may configure location-based recommendation information by using a picture including location data collected on a database. For example, the information configuration unit 420 may group the collected photos using location data. The information configuration unit 420 may configure a photo group for each location ID, but group photos in which a corresponding location ID is stored for each location ID or a location value of a region belonging to the corresponding location ID is stored. In addition, the information configuration unit 420 may group the collected photos into a plurality of categories according to the content of the photos through image analysis technology using artificial intelligence (AI) or the like. In addition to image analysis technology, it is also possible to classify photos into various categories by using attribute information included in photos or tags directly input by the user (eg, food menu names are input in the case of food photos). For example, photos may be classified into background photos and food photos, and food photos may be subdivided and reclassified for each menu. A category for grouping photos may be determined in advance according to a service type or characteristic, and for example, may be divided into themes of various subjects, such as food, sights, and entertainment. Accordingly, the information configuration unit 420 may preferentially group photos including location data by location ID, and further group photos into several categories through image analysis and have similarities within a certain range within each category. You can regroup the same photos. As such, the information configuration unit 420 may configure location-based recommendation information by grouping the collected photos based on location IDs and/or image analysis results. The information configuration unit 420 groups the collected photos into a photo group by location ID based on the location ID, and regroups the photo group by location ID into a plurality of categories based on the image analysis result, thereby providing location-based recommendation information can be configured.

In step S540 , when a request for a location-based recommendation service is received from the user of the first electronic device 110 , the information providing unit 440 responds to the map through a map screen including the location specified by the user. It is possible to provide location-based recommendation information. The location specified by the user may mean the current location of the user obtained from the first electronic device 110 or a location directly selected by the user. When the user's service request is received, the information providing unit 440 may identify a location specified by the user at the time the service request is received and provide a map screen centered on the location, in this case, the corresponding location through the map screen. Photos grouped by location ID in the map may be provided as location-based recommendation information. The user's service request may include information on the category selected by the user. In this case, the information providing unit 440 may select and recommend only the photos classified into the category selected by the user from among the photos grouped by the location ID on the map. . And, when the user requests a location-based recommendation service in a specific community, the information providing unit 440 identifies the identification information of the community in which the user requested the location-based recommendation service and the user's social network information in the corresponding community, Among the photos grouped by location ID, photos uploaded by people belonging to the corresponding community can be selected and provided as location-based recommendation information. For example, if a user requests a location-based recommendation service in a specific group chat room of a messenger, only photos uploaded by people who have participated in the group chat room can be recommended. It is possible to recommend photos uploaded by other users related to the . The information providing unit 440 provides grouped photos for each location ID within a certain distance based on the location through the map screen of the location specified by the user, but the user and the user in the community requesting the service It is possible to select and recommend photos uploaded by people who have been set (other users related to the user who requested the service according to social network information).

When the information providing unit 440 provides a plurality of photo groups as location-based recommendation information (for example, when a plurality of photo groups for each location ID exist on a map screen including a location specified by a user, or a specific location If a plurality of photo groups of different categories exist for ID), the ranking according to the recommendation score may be reflected. At this time, the ranking calculation unit 430 calculates a recommendation score or a category score for each photo group with respect to a location ID or a category (classified using a picture, such as an image analysis result of a picture). It can be calculated by giving a weight to at least one of the number of photos in each group, the number of views, the freshness (time), and the proximity (location). For that group of photos, the higher the number of photos uploaded by users, the higher the number of views of the photos, the more recently uploaded photos (shorter time elapsed since upload) and/or the location ID is set by the user. A higher recommendation score or category score may be calculated as the location is closer to the specified location. Among the above factors, the number of views and freshness may differ for each photo belonging to a group, so the number of views of a photo group is the average value of the number of views of the photos included in the group or the highest number of views among the photos included in the group and the freshness of the photo group may be determined using the upload time of the most recently uploaded photo among photos included in the corresponding group. In this case, it is possible not only to give a certain weight to all elements, but also to apply different weights according to the elements. For example, weights of 40%, 30%, 20%, 10% or 20, 10, 10, 1 can be applied respectively for number of photos, views, freshness (time), and proximity (location), and different weights for proximity (location). A lower weight may be given to the element. As another example, different weights may be applied to each element according to the type or characteristic of a category that is a criterion for classifying photos. For example, in the case of food photos, the highest weight may be given to freshness, and in the case of background photos, the highest weight may be given to the number of photos. Accordingly, the information providing unit 440 provides a photo group for each location ID within a certain distance based on the location through the map screen of the location specified by the user as location-based recommendation information, but in the ranking calculator 430 By reflecting the calculated ranking, a photo group may be provided in the order of the recommended score. The information providing unit 440 also, when the photo group by location ID is regrouped into a plurality of categories, reflects the ranking according to the category score for the photo groups for each category with respect to the plurality of categories in the order of the category score. can provide

6 is an exemplary view for explaining a process of assigning a location ID to a photo according to an embodiment of the present invention.

When the user of the first electronic device 110 uploads a photo including location data through a community such as a messenger or SNS, the collection unit 410 uses the photo including location data as content usable in a location-based recommendation service. collect As shown in FIG. 6 , it is assumed that the entire map 600 is divided into a plurality of regions of a predetermined size and a location ID is assigned to each divided region. In this case, the collecting unit 410 does not store the GPS coordinate value 601 when the GPS coordinate value 601 indicating the exact location of the first electronic device 110 is included in the photo in the process of collecting the photo. The location ID assigned to the area 610 to which the value 601 belongs may be stored.

The present invention is not limited thereto, and in the process of collecting the photos, the GPS coordinate values 601 included in the photos are stored as they are, and then, the photos including the GPS coordinate values 601 are stored in the grouping process of the information configuration unit 420 . It is also possible to classify into photo groups for the location ID of the area 610 to which the corresponding GPS coordinate value 601 belongs.

7 is an exemplary diagram for explaining a process of classifying photos including location data according to an embodiment of the present invention.

The information configuration unit 420 may configure location-based recommendation information by grouping the collected photos based on location IDs and image analysis results. Referring to FIG. 7 , the information configuration unit 420 may first group the photos collected on the database 151 based on the location ID (eg, location 1 group, location 2 group, ?). In addition, the information configuration unit 420 may regroup the photo groups for each location ID into detailed categories using photos belonging to each photo group. In this case, the regrouping refers to segmenting and classifying photos classified by location ID into one or more category depths, and may be divided into a first level category, a second level category, and ? according to the depth. For example, the information configuration unit 420 analyzes each image of the photo belonging to the location 1 group (location ID = 'location 1'), and a background photo group (first level category = 'background') and a food photo group (1st level category = 'food'), and can be subdivided and regrouped for each menu for each food photo group (eg, menu 1 group (2nd level category = 'menu 1'), menu 2 groups (2nd level category = 'menu2'), etc.).

Accordingly, the information configuration unit 420 may basically classify photos including location data by location ID and group them into photo groups by location ID, and in the group by location ID, detail according to the content of the photo through image analysis. You can regroup by category.

8 to 9 are diagrams illustrating a screen for requesting a location-based recommendation service according to an embodiment of the present invention.

8 shows a chat room screen 800 of a messenger, which is one of the Internet communities. The chat room screen 800 is a user interface screen through which a user can exchange messages with a counterpart or exchange various contents such as photos, videos, and voices. It may be a group chat room. As shown in FIG. 8 , the chat room screen 800 may include a recommendation menu 801 for a user to request a location-based recommendation service.

9 shows a chat room list screen 900 of a messenger. As shown in FIG. 9 , the chat room list screen 900 may include a chat room list 910 in which chat rooms in which the user exchanges messages or contents with the other party are arranged. For example, the chat room list 910 may be sorted in descending order based on message transmission/reception time, which is one of the existing sorting criteria. there is. In this case, the chat room list screen 900 may include a recommendation menu 901 for the user to request a location-based recommendation service.

The chat room screen 800 or the chat room list screen 900 may additionally include a menu through which the user can select a category of information to be recommended.

8 and 9 are exemplary and not limited thereto, and although detailed illustration is omitted, the user can use the 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 SNS. You can provide a menu for access.

10 to 11 show examples of screens for providing location-based recommendation information according to an embodiment of the present invention.

When the user operates the recommended menus 801 and 901 on the chat room screen 800 or the chat room list screen 900, as shown in FIG. 10, a map screen centered on the location 1011 specified by the user ( 1000) may be displayed. The map screen 1000 is composed of a map indicating the current location of the user or the location selected by the user. Recommendation information 1020 based on the location 1011 specified by the user may be exposed on the map screen 1000 , and among all location IDs included in the map screen 1000 , for each location ID where a photo group exists Recommendation information 1020 may be displayed. For example, the recommended information 1020 is information about a photo group, and at least one of representative photo(s) arbitrarily selected from the group and the number 1021 of photos classified into the group may be displayed.

When the user requests a location-based recommendation service through the chat room screen 800 in which the chat partner is specified, only photos uploaded by the other person participating in the chat room may be provided as the recommendation information 1020, and an interface in which the chat partner is not specified When a location-based recommendation service is requested on the screen (eg, the chat room list screen 900 or the friend list screen (not shown)) or the community screen, all people (all friends) who have a predetermined relationship with the user within the community are uploaded. One picture may be provided as the recommendation information 1020 .

When there are two or more photo groups for each location ID included in the map screen 1000 , a ranking according to a recommendation score for a photo group for each location ID may be reflected and provided as the recommendation information 1020 . In this case, the recommendation score may be calculated by weighting at least one of the number of photos, the number of views, the freshness (time), and the proximity (location) of each photo group. For example, on the map screen 1000 , as the recommendation score or the number of views increases, the recommendation information 1020 for the photo group by location ID may be displayed larger.

In addition, when a photo group by location ID is reclassified into categories, the recommended information 1020 for each category may be displayed on the map screen 1000 . When a category is selected when a user requests a service, only a photo classified into the category selected by the user from among photos grouped by location ID in the map screen 1000 may be provided as the recommendation information 1020 .

Referring to FIG. 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 list of photos 1110 grouped by the location ID may be displayed. . For example, when the user selects the 'food' category, the detailed service screen 1100 may display a photo list 1110 classified as 'food' among the photo groups of the corresponding location ID. In this case, the photo list 1110 is made up of photos belonging to the 'food' category, and in this case, it can be displayed by grouping each sub-category, for example, menus (menu 1, menu 2, and menu 3).

In addition, in the photo list 1110 , a ranking according to a category score may be reflected for a photo group for each detailed category. In this case, the recommendation score can be calculated by giving weight to at least one of the number of photos, number of views, freshness (time), and proximity (location) of each photo group. For example, the photo list 1110 is A category score of a photo group may be displayed in an order of being sorted in ascending order.

Therefore, the user can check which places are popular with acquaintances in the community or chat room counterparts through the map screen of the current location or directly selected location in an environment using a community such as messenger or SNS, and in the case of food photos, which menu You can check if it is popular.

In the above description, a picture has been used as an example, but any type of content that can be provided as location-based recommendation information is applicable.

As described above, according to embodiments of the present invention, location-based recommendation information can be effectively provided by using content including location data among content uploaded through an Internet community for user-to-user communication. In particular, according to embodiments of the present invention, it is possible to recommend content actually 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.

The device described above may be implemented as a hardware component, a software component, and/or a combination of the hardware component and the software component. For example, the apparatus and components described in the embodiments may include a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), and a programmable logic unit (PLU). It may be implemented using one or more general purpose or special purpose computers, such as a logic unit, 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 executed on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that can include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

Software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be embodied in any tangible machine, component, physical device, computer storage medium or device for interpretation by or providing instructions or data to the processing device. there is. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. In this case, the medium may be to continuously store a program executable by a computer, or to temporarily store it for execution or download. In addition, the medium may be various recording means or storage means in the form of a single or several hardware combined, it is not limited to a medium directly connected to any computer system, and may exist distributed over a network. Examples of the medium include a hard disk, a magnetic medium such as a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floppy disk, and those configured to store program instructions, including ROM, RAM, flash memory, and the like. In addition, examples of other media may include recording media or storage media managed by an app store that distributes applications, sites that supply or distribute other various software, and servers.

Modes for carrying out the invention

As described above, although the embodiments have been described with reference to the limited embodiments and drawings, various modifications and variations are possible from the above description by those skilled in the art. For example, the described techniques are performed in an order different from the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

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

Claims (20)

In the computer-implemented method of providing recommended information,
collecting photos uploaded through an Internet community and including location data;
configuring location-based recommendation information by grouping the collected photos using the location data; and
When a request for a location-based recommendation service is received from an electronic device through the Internet community, a map screen including a location specified by a user of the electronic device is provided, but grouped for location data in the map through the map screen Steps to provide photos
including,
The step of providing the grouped photos,
receiving a request for the location-based recommendation service through an interface screen in which at least one conversation partner is specified among the interface screens of the Internet community; and
Selecting and providing a photo uploaded by the conversation partner from among the photos grouped with respect to the location data in the map according to the received request
including,
The configuring step is
Classifying the collected photos into photo groups for a location ID assigned to an area corresponding to the location data of the collected photos
including,
The step of providing the grouped photos,
For each location ID where a photo group exists among the location IDs included in the map screen, information on the photo group of the location ID is displayed as the recommended information, but the latest information according to the number of photos, views, and photo upload time of each photo group Displaying information about a photo group for each location ID differently on the map screen based on at least one of last name and proximity to the location specified by the user
A method of providing recommended information, characterized in that According to claim 1,
The collecting step is
Storing the location ID assigned to the area corresponding to the location data of the collected photo with respect to the collected photo. delete According to claim 1,
A location ID is assigned to each segmented area of the map,
The configuring step is
Constructing a photo group for each location ID, and grouping a photo including a corresponding location ID for each location ID or a photo including the location data in an area to which the location ID is assigned into a photo group by location ID , how to provide recommendations. 5. The method of claim 4,
The configuring step is
and regrouping the photo group for each location ID into a plurality of categories according to content of photos belonging to the photo group through image analysis. 5. The method of claim 4,
The configuring step is
and regrouping the photo group for each location ID into a plurality of categories using attribute information or tag information included in photos belonging to the photo group. According to claim 1,
The step of providing the grouped photos,
Selecting and providing at least some of the photos grouped by the location data based on the user's identification information of the Internet community requesting the location-based recommendation service and the user's social network information in the Internet community , how to provide recommendations. 8. The method of claim 7,
The step of providing the grouped photos,
When the user requests the location-based recommendation service through a specific chat room of the Internet community, selecting and providing photos uploaded by people participating in the chat room from among photos grouped for location data in the map , how to provide recommendations. 8. The method of claim 7,
The step of providing the grouped photos,
When the user requests the location-based recommendation service without specifying a conversation partner through the Internet community, the user according to the user's social network information in the Internet community among photos grouped with respect to the location data in the map and providing a photo uploaded by at least one other user associated with the method. 7. The method according to claim 5 or 6,
The method of providing the recommended information is
When a plurality of photo groups by location ID exist on the map screen, the number of photos in each photo group, number of views, freshness according to photo upload time, location specified by the user for the plurality of photo groups by location ID Comprising the step of calculating a recommendation score based on at least one factor of proximity to
The step of providing the grouped photos,
and providing the plurality of photo groups for each location ID by reflecting the ranking according to the recommendation score. 11. The method of claim 10,
The calculating step is
A recommendation score for each photo group is calculated by giving weight to at least two or more factors among the number of photos in each photo group, the number of views, the freshness according to the upload time of the photo, and the proximity to the location specified by the user. A method of providing recommended information, comprising the step of: 11. The method of claim 10,
The configuring step is
Regrouping the photo group by location ID into a plurality of categories using photos belonging to the photo group,
The method of providing the recommended information is
Calculating a category score based on at least one of the number of photos in the photo group for each category, the number of views, the freshness according to the photo upload time, and the proximity to the location specified by the user for the plurality of categories; including,
The step of providing the grouped photos,
and providing photo groups for each category with respect to the plurality of categories by reflecting the ranking according to the category score. A computer program stored in a computer-readable recording medium in combination with a computer to cause the computer to execute the method for providing recommended information according to any one of claims 1, 2, and 4 to 9. A computer-readable recording medium, characterized in that a program for executing the method for providing recommended information according to any one of claims 1, 2, and 4 to 9 on a computer is recorded. In the computer-implemented recommendation information providing system,
at least one processor; and,
a memory coupled to the at least one processor and including instructions executable by the at least one processor
including,
the at least one processor,
the process of collecting photos uploaded through an internet community and containing location data;
configuring location-based recommendation information by grouping the collected photos using the location data; and
When a request for a location-based recommendation service is received from an electronic device through the Internet community, a map screen including a location specified by a user of the electronic device is provided, but grouped for location data in the map through the map screen process of providing photos
process the
The process of providing the grouped photos is,
receiving a request for the location-based recommendation service through an interface screen in which at least one conversation partner is specified among the interface screens of the Internet community;
Selecting and providing the photo uploaded by the conversation partner from among the photos grouped with respect to the location data in the map according to the received request
including,
The construction process is
Classifying the collected photos into photo groups for location IDs assigned to areas corresponding to the location data of the collected photos
including,
The process of providing the grouped photos is,
For each location ID where a photo group exists among location IDs included in the map screen, information on a photo group of the location ID is displayed as the recommended information, but the latest information according to the number of photos, views, and photo upload time of each photo group Displaying information about a photo group for each location ID differently on the map screen based on at least one of last name and proximity to the location specified by the user
Including, recommendation information providing system. 16. The method of claim 15,
A location ID is assigned to each segmented area of the map,
The process of configuring the location-based recommendation information includes:
Constructing a photo group for each location ID, including grouping a photo including a corresponding location ID for each location ID or a photo including the location data of an area to which the location ID is assigned into a photo group by location ID, Recommendation information provision system. 17. The method of claim 16,
The process of configuring the location-based recommendation information includes:
and regrouping the photo group for each location ID into a plurality of categories according to content of photos belonging to the photo group through image analysis. 16. The method of claim 15,
The process of providing the grouped photos is,
Based on the identification information of the Internet community in which the user requested the location-based recommendation service and the user's social network information in the Internet community, among photos grouped for the location data in the map, the user in the Internet community A system for providing recommended information, comprising selecting and providing photos uploaded by at least one other user related to the user according to social network information. 17. The method of claim 16,
the at least one processor,
When a plurality of photo groups by location ID exist on the map screen, the number of photos in each photo group, number of views, freshness according to photo upload time, location specified by the user for the plurality of photo groups by location ID The process of calculating a recommendation score based on at least one factor among proximity to
process the
The process of providing the grouped photos is,
Including providing the plurality of photo groups for each location ID by reflecting the ranking according to the recommendation score, the recommendation information providing system. 20. The method of claim 19,
The process of configuring the location-based recommendation information includes:
Regrouping the photo group by location ID into a plurality of categories using photos belonging to the photo group,
the at least one processor,
A process of calculating a category score based on at least one of the number of photos of each category, the number of views, the freshness according to the photo upload time, and the proximity to the location specified by the user for the plurality of categories
process the
The process of providing the grouped photos is,
A system for providing recommended information, including providing photo groups for each category with respect to the plurality of categories by reflecting the ranking according to the category score.

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