JP7345020B2 - Recommendation method and system using content including location data - Google Patents

Description

The following description relates to techniques for providing location-based services.

With the popularization of infrastructure for generating location-based content, such as smartphones and global positioning systems (GPS), the use of location-based services is rapidly increasing.

The types of content that users can use in location-based services are diverse, such as photos, music, videos, games, real-time information content, etc., and the variety of types continues to increase.

As an example of a technology that provides location-based services, Patent Document 1 (registration date: September 23, 2015) describes a technology that provides affiliated store information to user terminals in real time based on location information of the user's current location. , a technology has been disclosed that provides user terminals with information regarding discounts and mileage usage offered by the relevant affiliated store to attract customers, and affiliated store information regarding the current number of customers.

Korean Registered Patent No. 10-1556559

To provide a method and system that can provide location-based recommendation information by using content that includes location data among content uploaded to an Internet community for users to communicate with each other.

To provide a method and system capable of recommending content actually uploaded by a person who has a predetermined relationship with a user in an Internet community on a map of a location specified by the user.

A method for providing recommendation information implemented by a computer, comprising: collecting photos uploaded to an Internet community and including location data; and configuring location-based recommendation information by grouping collected photos using location data. , and when a request for a location-based recommendation service is received from an electronic device in the Internet community, a map screen containing the location specified by the user of the electronic device is provided, and grouping is performed on the map screen for the location data in the corresponding map. Provided is a method for providing recommendation information, including the step of providing a photograph that has been selected.

According to one aspect, collecting may include recording, for the collected photos, a location ID assigned to a region corresponding to location data of the collected photos.

According to other aspects, configuring may include classifying the collected photos as photo groups for location IDs assigned to regions corresponding to 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 step includes configuring a photo group for each location ID, and for each location ID, a photo group including a corresponding location ID or a corresponding location ID. The method may include the step of grouping photos including location data of the area to which the area is assigned as a photo group by location ID.

According to still another aspect, the step of configuring may include performing an image analysis of the photo groups by location ID and regrouping the photos into a plurality of categories based on the content of the photos belonging to the photo groups.

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

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

In addition, according to another aspect, when a user requests a location-based recommendation service in a particular chat room of the Internet community, the provision of photos grouped against the location data in the map will be provided to the chat room. The method may include the step of selecting and providing photos uploaded by a person who has uploaded the image.

According to another aspect, when a user requests a location-based recommendation service without specifying a chat partner in the Internet community, the provision of the Internet community may include providing photos uploaded by at least one other user associated with the user based on the user's social network information at the user's social network information.

According to another aspect, when a plurality of photo groups for each location ID exist on a map screen, the method for providing recommendation information includes the number of photos in each photo group, the number of inquiries, The step includes calculating a recommendation score based on at least one of the following: recency based on photo upload time and proximity to a location specified by the user; The method may include reflecting and providing a ranking based on scores.

According to another aspect, the calculating step takes into account at least two of the following factors: the number of photos in each photo group, the number of inquiries, the latestness based on the upload time of the photos, and the proximity to the location specified by the user. The method may include the step of calculating a recommendation score for each photo group by assigning a weight value to each photo group.

According to still another aspect, the step of configuring includes the step of regrouping the photo group by location ID into a plurality of categories using photos belonging to the photo group, and the recommendation information providing method includes a step of regrouping the photo group by location ID into a plurality of categories. , calculating a category score based on at least one of the following: the number of photos in each category of photo groups, the number of inquiries, recency based on photo upload time, and proximity to a location specified by the user; The step of determining may include providing a group of photos for each category, reflecting rankings based on category scores, for a plurality of categories.

A computer program stored in a computer-readable storage medium is provided to be coupled to a computer and cause the computer to execute a recommendation information providing method.

To provide a computer-readable storage medium, characterized in that a program for causing a computer to execute a recommendation information providing method is stored.

A computer-implemented recommendation information providing system including 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 to and including location data, configuring location-based recommendation information by grouping the collected photos using location data, and receiving a request for location-based recommendation service from an electronic device in an Internet community. Recommendation information that operates when executing an instruction that provides a map screen that includes the location specified by the user of the electronic device and provides grouped photos for the location data in the map on the map screen if the user of the electronic device Provide a delivery system.

According to embodiments of the present invention, location-based recommendation information can be efficiently provided by using content that includes location data among content uploaded to an Internet community for users to communicate with each other. I can do it.

According to an embodiment of the present invention, content actually uploaded by a person who has a predetermined relationship with the user in the Internet community can be recommended on a map of the location specified by the user.

1 is a diagram illustrating an example of a network environment in an embodiment of the present invention. FIG. FIG. 2 is a block diagram for explaining the internal configuration of an electronic device and a server in an embodiment of the present invention. 1 is a diagram illustrating an example of a location-based recommendation service environment in an embodiment of the present invention; FIG. FIG. 3 is a diagram illustrating an example of components that a server processor may include in an embodiment of the present invention. 3 is a flowchart illustrating an example of a method that a server may perform in an embodiment of the invention. FIG. 3 is an exemplary diagram for explaining a process of assigning a location ID to a photograph in an embodiment of the present invention. FIG. 3 is an exemplary diagram illustrating a process of classifying photos including location data according to an embodiment of the present invention. FIG. 3 is a diagram illustrating an example screen on which a location-based recommendation service can be requested in an embodiment of the present invention. FIG. 3 is a diagram illustrating an example screen on which a location-based recommendation service can be requested in an embodiment of the present invention. FIG. 3 is a diagram illustrating an example screen for providing location-based recommendation information in an embodiment of the present invention. FIG. 3 is a diagram illustrating an example screen for providing location-based recommendation information in an embodiment of the present invention.

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

Embodiments of the present invention relate to techniques for providing location-based services, and more particularly, to methods and systems that can provide location-based recommendation information using content that includes location data.

Embodiments including the matters specifically disclosed herein can provide location-based recommendation information using content including location data, thereby improving efficiency, effectiveness, and convenience. Considerable advantages can be achieved in terms of performance, cost savings, etc.

FIG. 1 is a diagram showing an example of a network environment in an embodiment of the present invention. The network environment of FIG. 1 shows an example including multiple electronic devices 110, 120, 130, 140, multiple servers 150, 160, and a network 170. Such FIG. 1 is only an example for explaining the invention, and the number of electronic devices and the number of servers are not limited as shown in FIG. 1.

The plurality of electronic devices 110, 120, 130, and 140 may be fixed terminals or mobile terminals realized by computer devices. Examples of the plurality of electronic devices 110, 120, 130, and 140 include smartphones, mobile phones, tablets, navigation systems, PCs (personal computers), notebook PCs, digital broadcasting terminals, PDAs (personal digital assistants), and PMPs (portable devices). Multimedia Player), etc. For example, the first electronic device 110 may communicate with other electronic devices 120, 130, 140 and/or servers 150, 160 via the network 170 using wireless or wired communication methods.

The communication method is not limited, and is not limited to communication methods that utilize communication networks that can be included in the network 170 (for example, mobile communication networks, wired Internet, wireless Internet, and broadcasting networks), as well as communication methods that utilize short distances between devices. Wireless communications may also be included. For example, the network 170 is a PAN (personal area network), a LAN (local area network), a CAN (campus area network), a MAN (metropolitan area network), or a WAN (wide area network). e area network), BBN (broadband network), the Internet, etc. may include any one or more of the networks. Additionally, network 170 may include any one or more of network topologies including, but not limited to, a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree or a hierarchical network, and the like. It will not be done.

Servers 150, 160 are each implemented by one or more computing devices that communicate with multiple electronic devices 110, 120, 130, 140 via network 170 to provide instructions, code, files, content, services, etc. It's fine. For example, the server 160 may provide a file for installing an application to the first electronic device 110 connected via the network 170. In this case, the first electronic device 110 may install the application using a file provided from the server 160. The first electronic device 110 also connects to the server 150 under the control of an operating system (OS) and at least one program (for example, a browser or the installed application), and provides services and content provided by the server 150. You may receive an offer. For example, when the first electronic device 110 sends a service request message to the server 150 via the network 170 under the control of an application, the server 150 may send a code corresponding to the service request message to the first electronic device 110. , the first electronic device 110 may provide content to the user by configuring and displaying a code-based screen under the control of the application.

FIG. 2 is a block diagram for explaining the 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 will be described as an example of one electronic device, and the internal configuration of the server 150 will be described as an example of one server. Other electronic devices 120, 130, 140 and server 160 may also have the same or similar internal configurations.

The first electronic device 110 and the server 150 may include a memory 211, 221, a processor 212, 222, a communication module 213, 223, and an input/output interface 214, 224. The memories 211 and 221 are computer-readable recording media, and may include non-transitory mass storage devices such as RAM (random access memory), ROM (read only memory), and disk drives. Furthermore, an operating system and at least one program code (for example, a code for an application installed and executed in the first electronic device 110) may be recorded in the memories 211 and 221. Such software components may be loaded from a computer readable storage medium separate from the memory 211, 221. Such other computer-readable recording media may include computer-readable recording media such as floppy drives, disks, tapes, DVD/CD-ROM drives, memory cards, and the like. In other embodiments, the software components may be loaded into the memory 211, 221 through a communication module 213, 223 that is not a computer readable storage medium. For example, at least one program may be a computer program (as an example, as described above) that is installed by a file provided over network 170 by a developer or a file distribution system that distributes application installation files (such as server 160, as described above). may be loaded into the memory 211, 221 based on the application (used by the user).

Processors 212, 222 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. Instructions may be provided to the processor 212, 222 by the memory 211, 221 or the communication module 213, 223. For example, processors 212, 222 may be configured to execute instructions received according to program code recorded on a storage device, such as memory 211, 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 via the network 170, or may provide a function for the first electronic device 110 and the server 150 to communicate with each other, or may provide a function for communicating with other electronic devices (for example, the second electronic device 120). Alternatively, a function for communicating with another server (for example, server 160) may be provided. As an example, a request (for example, a search request) generated by the processor 212 of the first electronic device 110 according to a program code recorded in a storage device such as the memory 211 is transmitted via the network 170 under the control of the communication module 213. may be transmitted to the server 150. On the contrary, control signals, instructions, contents, files, etc. provided under the control of the processor 222 of the server 150 are sent to the first electronic device via the communication module 223 and the network 170, and then through the communication module 213 of the first electronic device 110. The information may be received by device 110. For example, control signals, commands, etc. of the server 150 received through the communication module 213 may be transferred to the processor 212 and the memory 211, and content, files, etc. may be transferred to a storage medium that the first electronic device 110 may further include. May be remembered.

Input/output interface 214 may be a means for interfacing with input/output device 215. For example, input devices may include a device such as a keyboard or mouse, and output devices may include a device such as a display for displaying a communication session of an application. As another example, input/output interface 214 may be a means for interfacing with a device that has integrated input and output functionality, such as a touch screen. As a more specific example, when the processor 212 of the first electronic device 110 processes instructions of a computer program loaded into the memory 211, it is configured to use data provided by the server 150 and the second electronic device 120. Service screens and content may be displayed on the display through the input/output interface 214. Input/output interface 214 may similarly output information configured using data provided by server 150 as processor 222 of server 150 processes instructions of a computer program loaded into memory 221.

Also, in other embodiments, the first electronic device 110 and the server 150 may include more components than those in FIG. 2. However, most prior art components need not be clearly illustrated. 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 include a transceiver, a GPS (Global Positioning System) module, a camera, various sensors, a database, etc. It may further include other components such as. As a more specific example, if the first electronic device 110 is a smartphone, the smartphone typically includes an acceleration sensor, a gyro sensor, a camera, various physical buttons, buttons using a touch panel, and input/output ports. It is understood that various components such as a vibrator for vibration, etc. may be further included in the first electronic device 110.

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

The server 150 according to this embodiment may include a computer-implemented recommendation information providing system. The server 150 provides a location-based recommendation service to a plurality of electronic devices 110, 120, 130, and 140 that are clients, and is installed on the electronic devices 110, 120, 130, and 140. Recommendation information may be provided in response to a service request via a dedicated application or web/mobile site connection associated with the server 150.

Referring to FIG. 3, the server 150 may play the role of a recommendation server that provides a location-based recommendation service, and may be implemented in one service platform with a community server that provides a community service, or may be a separate service platform. A location-based recommendation service may be provided by linking with a community server implemented on the platform and collaborating with community services.

In this specification, a community may include all communication means on the Internet for users to communicate with each other, and may include, for example, messengers, SNS (social network service), and the like.

When a user sends content including location data as a message or registers it on an SNS, the corresponding content may be transmitted to a destination (another user or SNS) after the location data is removed. At this time, the server 150 may configure location-based recommendation information using content including location data as content uploaded to the Internet community, and provide this to the user who requested the location-based recommendation service. good.

In this specification, content may refer to all information provided via the Internet, and may include, for example, photos, images, videos, audio, documents, music, and the like. In the specific embodiment described below, a photograph will be exemplified and explained as a representative content, but the present invention is not limited to this.

FIG. 4 is a diagram illustrating an example of components that a processor of a server may include, in an embodiment of the invention, and FIG. 3 is a flowchart illustrating an example method.

In order for the server 150 to execute the recommendation information providing method according to FIG. 5, the processor 222 of the server 150 includes a collection unit 410, an information configuration unit 420, a ranking calculation unit 430, and a ranking calculation unit 430, as shown in FIG. An information providing section 440 may be included. Depending on the embodiment, components of processor 222 may be selectively included or excluded from processor 222. Also, depending on the embodiment, components of processor 222 may be separated or combined to express the functionality of processor 222.

Such processor 222 and components of processor 222 may control server 150 to perform steps 510-540 included in the recommendation information providing method of FIG. For example, processor 222 and components of processor 222 may be implemented to execute instructions from operating system code and at least one program code that memory 221 contains.

Here, the components of processor 222 may be representations of different functions of processor 222 that are executed by processor 222 according to instructions provided by program code stored on server 150. For example, collection unit 410 may be utilized as a functional representation of processor 222 that controls server 150 according to the instructions described above so that server 150 collects content including location data.

At step 510, processor 222 may read the necessary instructions from memory 221 loaded with instructions associated with controlling server 150. In this case, the read instructions may include instructions for controlling processor 222 to perform steps 520-540 described below.

In step 520, the collection unit 410 may collect photos including location data from among the photos uploaded by the plurality of electronic devices 110, 120, 130, and 140. When a user takes and uploads a photo including location data to an Internet community for users to communicate with each other, such as a messenger or SNS, the collection unit 410 collects the photo as content that can be used in a location-based recommendation service. may be collected. In the case of a user who has given permission for location sharing in advance, the location data of the electronic devices 110, 120, 130, 140 may be received along with the photo during the photo upload process, and by recording this on a database linked to the server 150. , may collect photos that include location data. At this time, the location data recorded on the database may be specific location values such as GPS coordinates of the electronic devices 110, 120, 130, and 140. Alternatively, the position ID (identity) may be a position ID (identity) indicating the area to which the corresponding position value belongs. To explain in more detail, a method may be used in which the entire map is divided into a plurality of regions and a unique location ID is assigned to each divided region, and in this case, the collection unit 410 takes a photo containing location data. Rather than recording the specific position value acquired by the electronic device for the user who uploaded the file, the position ID corresponding to the corresponding position value is recorded as approximate position information. Further, the position data may be a position value automatically obtained from an electronic device using GPS or the like, or may be position information directly input by the user. Furthermore, in the process of collecting photos including location data, the collection unit 410 records both identification information (for example, user ID) of the user who uploaded the photo and community identification information as information related to the photo. You may do so. At this time, the community identification information may be information about the community to which the user sent the photo, for example, in the case of Messenger, the chat room ID (individual or group) may correspond to the community identification information, and in the case of SNS, the corresponding community identification information. A community ID or the like may correspond to community identification information.

In step 530, the information configuration unit 420 may configure location-based recommendation information using photos 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 photo groups for each location ID, and may group photos in which a corresponding location ID is recorded for each location ID or a location value of an area belonging to the corresponding location ID is recorded. Further, the information configuration unit 420 may group the collected photos into a large number of categories based on the content of the photos using an image analysis technique using AI (artificial intelligence) or the like. In addition to image analysis technology, photos can be classified into multiple categories by utilizing attribute information included in the photo or tags entered directly by the user (for example, in the case of a food photo, entering the name of the food menu). It is also possible to do so. For example, photos may be classified into background photos and food photos, and in the case of food photos, they may be subdivided and reclassified by each menu. Categories for grouping photos may be predetermined according to the type or characteristics of the service, and may be divided into various themes such as food, attractions, playgrounds, etc. Therefore, the information configuration unit 420 may preferentially group photos including location data by location ID, and further group the photos into a number of categories by image analysis, and within each category, similar images within a certain range may be grouped. Identical photos with degrees may be regrouped. In this way, 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 photo groups by location ID based on the location ID, and regroups the photo groups by location ID into a plurality of categories based on the image analysis results. The location-based recommendation information may be configured as follows.

In step 540, when the information providing unit 440 receives a request for the location-based recommendation service from the user of the first electronic device 110, the information providing unit 440 provides the location-based recommendation corresponding to the corresponding map on the map screen including the location specified by the user. You may provide 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 grasp the location specified by the user at the time the service request was received and provide a map screen centered on the corresponding location. , on the map screen, photos grouped by location IDs within the corresponding map may be provided as location-based recommendation information. The user's service request may include information regarding the category selected by the user, and in this case, the information providing unit 440 may select a category that is classified into the category selected by the user from among the photos grouped by the location ID in the map. You may select and recommend only photos. Further, when the user requests a location-based recommendation service in a specific community, the information providing unit 440 grasps the identification information of the community from which the user requested the location-based recommendation service and the social network information of the user in the corresponding community. Of the photos grouped by location ID in the map, photos uploaded by people belonging to the corresponding community may 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 on Messenger, only photos uploaded by people who have participated in the group chat room may be recommended; When a service is requested, a photo uploaded by another user related to the user on the corresponding SNS, for example, a person with whom the user has a predetermined relationship (for example, a friend, colleague, family member, etc.) may be recommended. The information providing unit 440 described above provides photos grouped for each location ID within a certain distance based on the location on the map screen of the location specified by the user, and identifies the community for which the user has requested the service. may select and recommend photos uploaded by a person with whom the user has established a relationship (another user related to the user who requested the service based on social network information).

When providing 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 that includes a location specified by the user, or when a specific location ID (if there are multiple photo groups in different categories), rankings based on recommendation scores may be reflected. At this time, the ranking calculation unit 430 calculates a recommendation score or a category score for each photo group for the location ID or category (classified using the photo as in the image analysis result of the photo). The recommendation score or category score may be calculated by assigning a weight to at least one element among the number of photos in each group, the number of inquiries, recency (time), and adjacency (location). The more photos a user uploads for a given photo group, the higher the number of photos queried, the more recently the photos are uploaded (the less time has elapsed since uploading), and/or the more the user The closer the identified location and location ID are, the higher the recommendation score or category score may be calculated. Among the above factors, the number of inquiries and recency may differ for each photo belonging to a group, so the number of inquiries for a photo group is the average number of inquiries for photos included in the group, or the number of inquiries for a photo group. The recency of a photo group is determined by the upload time of the most recent photos among the photos included in the group. You can make a decision using At this time, not only can a fixed weight value be assigned to all elements, but also different weight values can be applied depending on the element. For example, weights of 40%, 30%, 20%, 10%, or 20, 10, 10, 1 are applied to number of photos, number of inquiries, recency (time), and adjacency (location), respectively. Adjacency may often be given a lower weight than other factors. As another example, different weight values may be applied to each element depending on the type or characteristics of the category that is the basis for classifying the photos. For example, in the case of food photos, the highest weight may be assigned to recency, and in the case of background photos, the highest weight may be assigned to the number of photos. Therefore, the information providing unit 440 provides, as location-based recommendation information, photo groups for each location ID within a certain distance from the location on the map screen of the location specified by the user, and the ranking calculation unit 430 Photo groups may be provided in the order of recommendation scores, reflecting the calculated rankings. Further, when the photo groups by location ID are regrouped into multiple categories, the information providing unit 440 reflects the ranking based on the category score in the photo groups for each category for the multiple categories, and arranges the photos in the order of the category scores. You may provide photo groups.

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

When the user of the first electronic device 110 uploads a photo that includes location data to a community such as a messenger or SNS, the collection unit 410 uploads the photo that includes location data as content that can be used in a location-based recommendation service. Collect as. As shown in FIG. 6, it is assumed that the overall map 600 is divided into a plurality of regions of a constant size, and a position ID is assigned to each divided region. At this time, in the process of collecting photos, if the photo includes a GPS coordinate value 601 indicating the exact location of the first electronic device 110, the collecting unit 410 does not record the GPS coordinate value 601, and stores the GPS coordinate value 601. The location ID assigned to the area 610 to which the image belongs may be recorded.

However, the present invention is not limited to this. In the process of collecting photos, the GPS coordinate values 601 included in the photos are recorded as they are, and then in the grouping process of the information configuration unit 420, the photos containing the GPS coordinate values 601 are recorded. It is also possible to classify the photos into groups corresponding to the position ID of the area 610 to which the corresponding GPS coordinate value 601 belongs.

FIG. 7 is an exemplary diagram illustrating 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 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 (for example, location 1 group, location 2 group, etc.). Thereafter, the information configuration unit 420 may regroup the photo groups for each location ID into detailed categories using the photos belonging to each photo group. At this time, regrouping means that photos classified by location ID are subdivided and classified by one or more category depths, and are divided into first level categories, second level categories, etc. by depth. May be classified. For example, the information configuration unit 420 analyzes the images of photos belonging to the position 1 group (position ID = “position 1”), and analyzes the images of the photos belonging to the position ID = “position 1” and the background photo group (first level category = “background”) and the food photo group (first level category = “background”). level category = "Food"), and the food photo group may be subdivided and regrouped by each menu (for example, Menu 1 group (second level category = "Menu 1"), Menu 2 group (e.g., 2nd level category = “Menu 2”).

Therefore, the information configuration unit 420 may basically classify photos including location data by location ID and group them into photo groups by location ID. May be regrouped into detailed categories based on content.

FIGS. 8 and 9 are diagrams illustrating example screens on which location-based recommendation services can be requested, according to an embodiment of the present invention.

FIG. 8 shows a chat room screen 800 of Messenger, one of the Internet communities. The chat room screen 800 is a user interface screen where a user can chat with a partner through messages or exchange various contents such as photos, videos, and audio, and is an individual chat room with only one partner. Of course, it may also be a group chat room in which multiple parties participate. 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.

FIG. 9 shows a messenger chat room list screen 900. As shown in FIG. 9, the chat room list screen 900 may include a chat room list 910 in which chat rooms in which users exchange messages and content with other parties are arranged. For example, the chat room list 910 may be sorted in descending order according to message sending/receiving time, which is one of the existing sorting criteria. In other words, the more recently the user sent and received messages, the higher the chat room may be arranged in the list. At this time, 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 and the chat room list screen 900 may additionally include a menu that allows the user to select the category of information that the user desires to recommend.

Since FIGS. 8 and 9 are illustrative, they are not limited to these, and specific diagrams are omitted; however, they may be used for a friend list screen including a messenger friend list or a community user interface such as an SNS. A menu for the user to access the location-based recommendation service may be provided on the screen or the like.

FIGS. 10 and 11 are diagrams showing examples of screens for providing location-based recommendation information in an embodiment of the present invention.

When the user operates the recommendation menus 801 and 901 on the chat room screen 800 or the chat room list screen 900, a map screen 1000 centered on the location 1011 specified by the user may be displayed, as shown in FIG. The map screen 1000 may be configured with a map showing the user's current location or a location selected by the user. The map screen 1000 may display recommendation information 1020 based on the location 1011 specified by the user. Among all the location IDs included in the map screen 1000, recommendation information is displayed for each location ID where a photo group exists. 1020 may be displayed. As an example, the recommendation information 1020 is information regarding a photo group, and includes at least one of (a plurality of) representative photos arbitrarily selected from the group and the number of photos 1021 classified into the group. May be displayed.

When a user requests a location-based recommendation service in a chat room screen 800 where a chat partner is specified, only the photos uploaded by the party participating in the corresponding chat room may be provided as recommendation information 1020, and the chat partner When a location-based recommendation service is requested on an unspecified interface screen (for example, the chat room list screen 900 or friend list screen (not shown), etc.) or a community screen, all the information that has a predetermined relationship with the user within the corresponding community Photos uploaded by people (all friends) may be provided as the recommendation information 1020.

When there are two or more photo groups classified by location ID included in the map screen 1000, rankings based on recommendation scores for the photo groups classified by location ID may be reflected and provided as recommendation information 1020. At this time, the recommendation score may be calculated by assigning a weighted value to at least one element among the number of photos in each photo group, the number of inquiries, recency (time), and adjacency (position). For example, in the map screen 1000, the higher the recommendation score or the greater the number of inquiries, the larger the recommendation information 1020 for the photo group by location ID may be displayed.

Further, when photo groups classified by location ID are reclassified into categories, recommendation information 1020 may be displayed by category on the map screen 1000. If a category is selected at the time of the user's service request, only the photos classified into the category selected by the user among the photos grouped by location ID in the map screen 1000 may be provided as the recommendation information 1020.

Referring to FIG. 11, when the user selects recommendation information 1020 for a specific location ID on the map screen 1000, a detailed service screen 1100 including a list of photos 1110 grouped by the corresponding location ID may be displayed. For example, when the user selects the "food" category, the detailed service screen 1100 may display a list 1110 of photos classified as "food" among the photo groups of the corresponding location ID. At this time, the photo list 1110 is composed of photos belonging to the "food" category, and may be shown grouped by detailed category, for example, menus (menu 1, menu 2, menu 3).

Further, the photo list 1110 may reflect rankings based on category scores for photo groups classified by detailed category. At this time, the recommendation score may be calculated by assigning a weight to at least one element of the number of photos in each photo group, the number of inquiries, recency (time), and adjacency (location). The list 1110 may be displayed in order of the category scores of the photo groups by category.

Therefore, in an environment where a user uses a community such as messenger or SNS, by using the map screen of the user's current location or a location directly selected by the user, the user can check the location, friends and chats on the corresponding community. You can check whether it is popular with the people in the room, and in the case of food photos, you can check what menu items are popular.

Although the above explanation has been given using photographs as an example, any type of content that can be provided as location-based recommendation information can be applied.

As described above, according to the embodiments of the present invention, location-based recommendation information can be efficiently used by using content that includes location data among the content uploaded to an Internet community for users to communicate with each other. can be provided to In particular, according to embodiments of the present invention, content actually uploaded by a person with a predetermined relationship with the user in the Internet community can be recommended on a map of a location specified by the user.

The apparatus described above may be realized by hardware components, software components, and/or a combination of hardware and software components. For example, the devices and components described in the embodiments include 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 (PLU), a microprocessor, or may be implemented using one or more general purpose or special purpose computers, such as various devices capable of executing and responding to instructions. A processing device may execute an operating system (OS) and one or more software applications that execute on the OS. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. Although for convenience of understanding, one processing device may be described as being used, those skilled in the art will appreciate that a processing device may include multiple processing elements and/or multiple types of processing elements. You will understand. For example, a processing device may include multiple processors or a processor and a controller. Other processing configurations are also possible, such as parallel processors.

Software may include computer programs, code, instructions, or a combination of one or more of these that configure a processing device or instruct a processing device, independently or collectively, to perform operations as desired. You may do so. The software and/or data may be embodied in a machine, component, physical device, computer storage medium or device of any kind for being interpreted by or providing instructions or data to a processing device. good. The software may be distributed on computer systems connected by a network, and may be recorded or executed in a distributed manner. The software and data may be recorded on one or more computer readable storage media.

Methods according to embodiments may be implemented in the form of program instructions executable by various computer means and recorded on computer-readable media. Here, the medium may be one that continuously records a computer-executable program, or one that temporarily records it for execution or download. Also, the medium may be a variety of recording or storage means in the form of a single or multiple hardware combinations, and is not limited to a medium directly connected to a computer system, but may be distributed over a network. It may also exist. Examples of media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and It may include ROM, RAM, flash memory, etc., and may be configured to record program instructions. Further, other examples of the medium include an application store that distributes applications, a site that supplies or distributes various other software, and a recording medium or storage medium managed by a server.

As mentioned above, although the embodiments have been described based on limited embodiments and drawings, those skilled in the art will be able to make various modifications and variations based on the above description. For example, the techniques described may be performed in a different order than in the manner described, and/or components of the systems, structures, devices, circuits, etc. described may be performed in a different form than in the manner described. Even when combined or combined, opposed or replaced by other components or equivalents, suitable results can be achieved.

Therefore, even if the embodiments are different, if they are equivalent to the scope of the claims, they fall within the scope of the appended claims.

Claims (11)

An information providing device that cooperates with a server that provides services of an Internet community, or provides services of the Internet community ,
a collection unit that collects content including location data;
an information configuration unit that configures location-based recommendation information based on content including the location data;
Information provision department and
Equipped with
The information provision department is
When a request for a location-based recommendation service is received from a first terminal of a first user in a chat room in which a chat partner of the Internet community is specified, a map screen including the location specified by the first user; providing location-based recommendation information generated based on content that corresponds to location data in the corresponding map and includes location data collected from a second terminal of a second user who has participated in the chat room;
When a request for the location-based recommendation service is received from the first terminal of the first user in a state where a chat partner is not specified in the Internet community, a map screen including the location specified by the first user, and a map screen on the map screen. providing location-based recommendation information generated based on content that corresponds to location data in a corresponding map and includes location data collected from a second terminal of a second user associated with the first user on the Internet community; ,
Information provision device. The information configuration unit configures location-based recommendation information by grouping the collected content using location data included in the content ,
The information providing unit provides the content grouped with respect to position data within the corresponding map on the map screen.
The information providing device according to claim 1. A location ID is assigned to each divided area of the map,
The information configuration unit groups content including a corresponding location ID or content including location data of an area to which the corresponding location ID is assigned, into a content group by location ID.
The information providing device according to claim 1 or 2. The information configuration unit performs an image analysis of the content groups for each location ID, and regroups the content into a plurality of categories based on the contents of the content belonging to the content group.
The information providing device according to claim 3. The information configuration unit regroups the content groups by location ID into a plurality of categories using attribute information and tag information included in content belonging to the content group.
The information providing device according to claim 3. The information providing unit performs grouping using location data based on identification information of the Internet community from which the first user has requested the location-based recommendation service and social network information of the first user in the Internet community. select and provide at least a portion of the content;
The information providing device according to claim 4 or 5. When a plurality of content groups classified by location ID exist on the map screen, the number of contents of each content group, the number of inquiries, the latestness according to content upload time, and the first user for each content group classified by location ID. a calculation unit that calculates a recommendation score based on at least one element of adjacency with the location specified by the user;
The information providing unit provides the content groups for each of the plurality of location IDs, reflecting the ranking based on the recommendation score.
The information providing device according to claim 4 or 5. The calculation unit weights at least two or more of the following: the number of contents in each content group, the number of inquiries, the latestness based on the upload time of the content, and the proximity to the location specified by the first user. Calculate the recommendation score for each content group by assigning a value.
The information providing device according to claim 7. The information configuration unit includes regrouping the content group by location ID into a plurality of categories using content belonging to the content group,
The calculation unit calculates, for the plurality of categories, at least one of the number of contents in the content group for each category, the number of inquiries, recency based on content upload time, and proximity to the location specified by the first user. Calculate category scores based on elements,
The information providing unit provides content groups by category for the plurality of categories, reflecting rankings based on the category scores.
The information providing device according to claim 7 or 8. The collection unit records, for the collected content, a location ID assigned to an area corresponding to location data of the collected content.
The information providing device according to any one of claims 1 to 9. A computer that cooperates with a server that provides services of the Internet community, or that provides services of the Internet community ,
a collection stage to collect content including location data;
an information configuration step of configuring location-based recommendation information based on content including the location data;
information provision stage;
A program that executes
In the information providing step, the computer:
When a request for a location-based recommendation service is received from a first terminal of a first user in a chat room in which a chat partner of the Internet community is specified, a map screen including the location specified by the first user; Providing location-based recommendation information generated based on content that corresponds to location data in the corresponding map and includes location data collected from a second terminal of a second user who has participated in the chat room;
When a request for the location-based recommendation service is received from the first terminal of the first user in a state where a chat partner is not specified in the Internet community, a map screen including the location specified by the first user, and a map screen on the map screen. Providing location-based recommendation information generated based on content that corresponds to location data in the corresponding map and includes location data collected from second terminals of second users associated with the first user on the Internet community. ,
program.

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