WO2018043860A1 - Dispositif de recommandation d'article de location au moyen d'un groupe de propension similaire et procédé d'utilisation associé - Google Patents

Dispositif de recommandation d'article de location au moyen d'un groupe de propension similaire et procédé d'utilisation associé Download PDF

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Publication number
WO2018043860A1
WO2018043860A1 PCT/KR2017/003313 KR2017003313W WO2018043860A1 WO 2018043860 A1 WO2018043860 A1 WO 2018043860A1 KR 2017003313 W KR2017003313 W KR 2017003313W WO 2018043860 A1 WO2018043860 A1 WO 2018043860A1
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group
user
rental
item
check
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PCT/KR2017/003313
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English (en)
Korean (ko)
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고재호
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에스케이플래닛 주식회사
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Publication of WO2018043860A1 publication Critical patent/WO2018043860A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0269—Targeted advertisements based on user profile or attribute
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0202—Market predictions or forecasting for commercial activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0255—Targeted advertisements based on user history
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0261—Targeted advertisements based on user location
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • G06Q50/40—

Definitions

  • the present invention relates to a device for recommending rental items using a similar propensity group and a method using the same. And it relates to a technology that can recommend the appropriate item to the user based on the rental history of the group.
  • Existing online shopping malls are intended for the sale of items, and provide a service that allows users to conveniently purchase desired items by inducing a purchase by providing a list of items suitable for users. For example, when a user selects a specific item from the item list, the user may purchase an item that the user wants online by providing an interface for inducing payment for the selected item.
  • An object of the present invention even if the rental history of the user using the item rental service is not enough to grasp the user's preference information to recommend the appropriate rental items.
  • an object of the present invention is to more accurately grasp the user's preference information by using a social network service in addition to the rental history in the item rental service.
  • an object of the present invention is to improve the use efficiency of the item rental service by recommending items that are expected to have high preference to the user.
  • a group generation unit for generating a plurality of groups associated with the user based on a social network service (Social Network Service) executed through a user terminal ;
  • a similarity propensity group extracting unit for extracting a similar propensity group for the user based on member information included in each of the plurality of groups;
  • a rental item recommending unit recommending a rental item to the user based on a rental history of an item rental service for at least one member included in the similarity group.
  • a group generator may generate the plurality of groups in consideration of whether members included in the group have subscribed to the item rental service.
  • the similarity propensity group extractor may include at least one member included in all of the plurality of groups in the similarity propensity group.
  • the plurality of groups are selected based on the number of conversations with the user in the social network service usage history of the user and a second selected based on the check-in place of the user in the social network service usage history. It can include a group.
  • the group generator may include: a first group generator configured to generate, as the first group, a conversation group having the most number of conversations during a preset conversation period among conversation groups registered in the social network service; And a second group generation unit configured to generate a second group including at least one user who has repeatedly checked in at least one reference number of times at a check-in place during a preset check-in period among users registered in the social network service. Can be.
  • the second group generator when there are a plurality of check-in locations, includes at least one user who has checked in to a plurality of check-in locations during the predetermined check-in period among the users registered in the social network service as a member.
  • a second group can be created.
  • the similarity propensity group extracting unit may extract a conversation group including a predetermined ratio of members included in the second group among the conversation groups as the similarity propensity group.
  • the rental item recommendation unit may recommend to the user at least one item having a history of rental by at least one member included in the similarity propensity group.
  • the rental item recommendation method in the present invention for achieving the above object, generating a plurality of groups associated with the user based on a social network service (Social Network Service) executed through the user terminal; Extracting a similar propensity group for the user based on member information included in each of the plurality of groups; And recommending the rental item to the user based on the rental history of the item rental service for at least one member included in the similarity propensity group.
  • Social Network Service Social Network Service
  • the generating may include generating the plurality of groups in consideration of whether members included in the group have subscribed to the item rental service.
  • the extracting may include at least one member included in the plurality of groups in the similar propensity group.
  • the plurality of groups are selected based on the number of conversations with the user in the social network service usage history of the user and a second selected based on the check-in place of the user in the social network service usage history. It can include a group.
  • the generating may include: generating, as the first group, a conversation group having the largest number of conversations during a preset conversation period among conversation groups registered in the social network service; And generating a second group including, as a member, at least one user who has repeatedly checked in at least one reference number of times at a check-in place during a preset check-in period among users registered in the social network service.
  • the step of generating a second group if there are a plurality of check-in places, the member of at least one user who has checked in all the plurality of check-in places during the predetermined check-in period among the users registered in the social network service
  • the second group may be generated to include.
  • the extracting may extract a conversation group including a predetermined ratio of members included in the second group among the conversation groups as the similarity propensity group.
  • the recommending may recommend to the user at least one item having a history borrowed by at least one member included in the similarity group.
  • the present invention even if the rental history of the user using the item rental service is not enough, it is possible to grasp the user's preference information and recommend the appropriate rental item.
  • the present invention can more accurately grasp the user's preference information by using the social network service in addition to the rental history in the item rental service.
  • the present invention can improve the use efficiency of the item rental service by recommending items expected to have high preference to the user.
  • FIG. 1 is a view showing a rental item recommendation system according to an embodiment of the present invention.
  • FIG. 2 is a block diagram illustrating an example of an apparatus for recommending rental items shown in FIG. 1.
  • FIG. 3 is a block diagram illustrating an example of a group generation unit illustrated in FIG. 2.
  • FIG. 4 is a diagram illustrating an item rental service according to an embodiment of the present invention.
  • FIG. 5 is a flowchart illustrating a rental item recommendation method using a similar propensity group according to an embodiment of the present invention.
  • FIG. 6 is an operation flowchart illustrating an example of a process of extracting a similar propensity group in a rental item recommendation method according to the present invention.
  • FIG. 7 is a flowchart illustrating another example of a process of extracting a similar tendency group in the method for recommending rental items according to the present invention.
  • FIG. 1 is a view showing a rental item recommendation system according to an embodiment of the present invention.
  • a rental item recommendation system may include a rental item recommendation device 110, terminals 120-1 to 120 -N, an item rental service server 130, and a network 140. It includes.
  • the rental item recommendation apparatus 110 shown in FIG. 1 is a terminal 120-1 to 120- when the item rental service server 130 provides the item rental service to the terminals 120-1 to 120-N. N) can recommend a rental item suitable for each user.
  • the rental item recommendation apparatus 110 and the item rental service server 130 are illustrated independently in FIG. 1, the rental item recommendation apparatus 110 may be included in the item rental service server 130 according to an exemplary embodiment. .
  • the rental item recommendation apparatus 110 generates a plurality of groups related to a user based on a social network service executed through the terminals 120-1 to 120 -N of the user.
  • a plurality of groups may be generated in consideration of whether members included in the group have subscribed to the item rental service.
  • the plurality of groups may include a first group selected based on the number of conversations with the user in the social network service usage history of the user and a second group selected based on the check-in place of the user in the social network service usage history. Can be.
  • the conversation group having the largest number of conversations during the preset conversation period among the conversation groups registered in the social network service may be generated as the first group.
  • a second group including at least one user who has repeatedly checked in at least a predetermined number of times at a user's check-in place during a preset check-in period may be generated as a member.
  • a second group including at least one user who has checked in a plurality of check-in places for a predetermined check-in period among the users registered in the social network service may be created as a member.
  • the rental item recommendation apparatus 110 extracts a similar propensity group for the user based on the member information included in each of the plurality of groups.
  • At least one member included in all of the plurality of groups may be included in the similar propensity group.
  • the conversation group in which the members included in the second group among the conversation groups are included in the preset ratio may be extracted as the similar propensity group.
  • the rental item recommendation apparatus 110 recommends a rental item to a user based on a rental history of an item rental service for at least one member included in a similar propensity group.
  • the user may recommend at least one item having a history of rental by at least one member included in the similarity group.
  • the terminals 120-1 to 120 -N access the item rental service server 130 or use a separate service application to use the item rental service provided by the item rental service server 130. To provide.
  • the terminals 120-1 to 120 -N are devices that can be connected to a communication network and can be connected to the item rental service server 130 or execute an application, and are a mobile phone, a portable multimedia player (PMP), and a mobile internet (MID).
  • PMP portable multimedia player
  • MID mobile internet
  • Various mobile communication specifications such as devices, smart phones, tablet PCs, notebooks, net books, personal digital assistants (PDAs), and telecommunication devices It may be a mobile terminal having a.
  • the terminals 120-1 to 120-N receive various information such as numbers and text information, set various functions, and receive signals input in connection with the function control of the terminals 120-1 to 120-N. It can be delivered to the controller through the input unit.
  • the input unit of the terminals 120-1 to 120 -N may include at least one of a keypad and a touch pad that generate an input signal according to a user's touch or manipulation.
  • the input unit of the terminals 120-1 to 120 -N is configured in the form of one touch panel (or touch screen) together with the display unit of the terminals 120-1 to 120 -N.
  • the display function can be performed at the same time.
  • the input unit of the terminals 120-1 to 120 -N may use any type of input means that may be developed in the future.
  • the display unit of the terminals 120-1 to 120 -N may display information on a series of operation states and operation results generated while performing the functions of the terminals 120-1 to 120 -N.
  • the display unit of the terminals 120-1 to 120 -N may display menus of the terminals 120-1 to 120 -N, user data input by the user, and the like.
  • the display unit of the terminals 120-1 to 120 -N includes a liquid crystal display (LCD), an ultra-thin liquid crystal display (TFT-LCD, thin film transistor LCD), and a light emitting diode (LED).
  • OLED Organic light emitting diode
  • AMOLED Active Matrix OLED
  • Retina display flexible display and flexible display (3 Dimension)
  • the display unit of the terminals 120-1 to 120 -N when configured in the form of a touch screen, the display unit of the terminals 120-1 to 120 -N functions as an input unit of the terminals 120-1 to 120 -N. Some or all of these may be performed.
  • the storage unit of the terminals (120-1 ⁇ 120-N) is a device for storing data, including a main storage device and an auxiliary storage device, the application required for the functional operation of the terminals (120-1 ⁇ 120-N) You can save the program.
  • the storage unit of the terminals 120-1 to 120 -N may largely include a program area and a data area.
  • the terminals 120-1 to 120 -N activate each function in response to a user's request, the terminals 120-1 to 120 -N execute respective application programs under the control of the controller to provide the respective functions.
  • the storage unit of the terminals 120-1 to 120-N may store an operating system and a program for providing a service for booting the terminals 120-1 to 120-N.
  • the storage unit of the terminals 120-1 to 120-N may store a content DB storing a plurality of contents and information of the terminals 120-1 to 120-N.
  • the content DB may include execution data for executing the content and attribute information on the content, and content usage information according to the content execution may be stored.
  • the information of the terminals 120-1 to 120 -N may include terminal specification information.
  • the communication unit of the terminal may perform a function for transmitting and receiving data through the network.
  • the communication unit of the terminals 120-1 to 120-N may include RF transmission means for up-converting and amplifying the frequency of the transmitted signal, and RF reception means for low-noise-amplifying and down-converting the received signal.
  • the communication unit of the terminals 120-1 to 120 -N may include at least one of a wireless communication module and a wired communication module.
  • the wireless communication module is a configuration for transmitting and receiving data according to a wireless communication method, and when the terminals 120-1 to 120 -N use wireless communication, a wireless network communication module, a wireless LAN communication module, and a wireless fan communication module.
  • the wired communication module is for transmitting and receiving data by wire.
  • the wired communication module may transmit and receive data by connecting to a network through a wire. That is, the terminals 120-1 to 120 -N may access a network by using a wireless communication module or a wired communication module, and may transmit and receive data through the network.
  • the controller of the terminals 120-1 to 120 -N may be a process device that drives an operating system (OS) and each component.
  • OS operating system
  • the controller may control the overall process of accessing the server.
  • the entire process of running the service application can be controlled according to the user's request, and at the same time, the service use request can be transmitted to the server at the time of executing the user authentication.
  • Information necessary for the terminal 120-1 to 120-N may be controlled to be transmitted together.
  • the controller of the terminals 120-1 to 120 -N may execute specific content stored in a storage unit of the terminals 120-1 to 120 -N according to a user's request. At this time, the controller may store the content usage history according to the execution of the content as the content usage information.
  • the item rental service server 130 is a server for providing an item rental service to the terminals 120-1 to 120 -N.
  • the item rental service server 130 provides a rental item to users of the terminals 120-1 to 120 -N and provides a rental fee. You can claim
  • the item rental service server 130 may be connected to the terminals 120-1 to 120-N of the users through the network 140 to provide an item rental service.
  • the item rental service server 130 may obtain information about rental items to be recommended to service users by communicating with the rental item recommendation apparatus 110 according to the present invention through the network 140.
  • the network 140 provides a path for transferring data between the rental item recommendation apparatus 110, the terminals 120-1 to 120 -N, and the item rental service server 130.
  • the concept encompasses all developable networks.
  • the network may be a wired / wireless local area network that provides communication of various information devices within a limited area, a mobile communication network that provides communication between each other, and between the mobile device and the outside of the mobile device. It may be either a satellite communication network or a wired or wireless communication network, or a combination of two or more.
  • the transmission standard of the network is not limited to the existing transmission standard, and may include all transmission standard that will be developed in the future.
  • FIG. 2 is a block diagram illustrating an example of an apparatus for recommending rental items shown in FIG. 1.
  • the rental item recommendation apparatus 110 illustrated in FIG. 1 may include a communication unit 210, a group generation unit 220, a similar propensity group extraction unit 230, a rental item recommendation unit 240, and a storage unit. 250.
  • the present invention is to provide a technology that can recommend a rental item through the rental history of other users with a similar tendency to the user even when the user first uses the item rental service or the history of renting the item is not sufficient. do.
  • the communication unit 210 may play a role of transmitting and receiving information necessary for recommending a rental item with a user terminal and an item rental service server through a communication network such as a network.
  • the communication unit 210 may receive a social network usage history for recommending rental items from a user terminal or a social network service server, and provide recommended item information to an item rental service server. have.
  • the group generator 220 generates a plurality of groups related to the user based on a social network service executed through the user terminal.
  • the social network service may correspond to an online service that establishes a network of connections between acquaintances of the user on the web or people who can share the fields and activities of interest to the user.
  • a social network service may include all kinds of services such as micro blogs, communities, blog messengers, etc., and a member or a user who registers a post based on a user's post, image, or location. It may also mean a service that can communicate with the people.
  • a plurality of groups related to the user may be generated based on posts or groups associated with the user through the social network service.
  • a plurality of groups may be generated in consideration of whether members included in the group have subscribed to the item rental service.
  • an object of the present invention may be to recommend the rental item to a user of a specific terminal by obtaining information of users having similar tendencies with the user of the specific terminal using the service among a plurality of users subscribed to the item rental service. . That is, when creating a plurality of groups, members belonging to each group may have to correspond to users subscribed to the item rental service.
  • the plurality of groups may include a first group selected based on the number of conversations with the user in the social network service usage history of the user and a second group selected based on the check-in place of the user in the social network service usage history. Can be.
  • the first group may be selected from the plurality of groups by checking the number of times of communicating with the user.
  • the second group may be selected using the location information tagged in the post that the user posts as the user's check-in location. have.
  • a second group may be selected based on a place where the user is checked in.
  • the first group and the second group may be selected as one or more than one.
  • the conversation group having the largest number of conversations during the preset conversation period among the conversation groups registered in the social network service may be generated as the first group.
  • the conversation groups in which the user conducted the conversation at least once a week from the present time are extracted, and among the extracted conversation groups
  • the conversation group having the largest number of conversations may be created as the first group.
  • the number of conversations may be measured based on the number of messages exchanged with each other.
  • the number of conversations may be measured by checking the occurrence frequency of the conversations by identifying the number of times the conversations started at a specific time point in the conversation group.
  • the user and the members of the conversation group A exchanged 100 messages for 10 minutes at 9 AM on January 1, 2016. Later, we can assume that 200 messages were sent and received again for about 20 minutes at 6 pm on January 1, 2016.
  • the number of conversations is measured based on the number of messages exchanged with each other, the number of conversations of the conversation group A on January 1, 2016 may be measured 300 times.
  • the number of conversations in conversation group A on January 1, 2016, is one conversation at 9 am plus one conversation at 6 pm, totaling 2 Can be measured in times.
  • the criterion for measuring the number of conversations may be used in various ways depending on the system in addition to the above-described method.
  • a second group including at least one user who has repeatedly checked in at least a predetermined number of times at a check-in place during a preset check-in period may be generated as a member.
  • the preset check-in period is one month and the preset reference number is five times
  • the user who has checked in at the check-in place of the user from the current one month before the user registered to the social network service is extracted.
  • a user who has checked in at least five times at a check-in place may be included as a member of the second group.
  • the number of check-in times may be measured in consideration of a time interval in which users registered to the social network service check-in at a check-in place in duplicate.
  • the check-in place C when the check-in place C is located during the movement of the user B, the check-in may be performed several times a day.
  • the wrong user When a second group is generated based on the check-in information, the wrong user may be included as the second group, so a rental item that is not appropriate for the user may be recommended.
  • a check-in time interval may be set in advance, and duplicate check-ins within a set check-in time interval may be ignored. That is, if it is assumed that the check-in time interval is 2 hours, the check-in that occurs repeatedly for the check-in place C until 3 pm after the user B is checked in at the check-in place C at 1 pm may be ignored and not recorded.
  • the check-in time interval may be freely set and changed according to the check-in location or the user.
  • the criterion for measuring the number of check-in may be used in various ways depending on the system in addition to the above-described method.
  • a second group including at least one user who has checked in to the plurality of check-in locations for a preset check-in period among the users registered in the social network service may be created as a member.
  • the preset check-in period is one month and the user has a total of ten check-in locations corresponding to A to J, at least once in each month from A to J among the users registered in the social network service from now to one month ago. May include all checked in users as members of the second group.
  • a second group including as a member at least one user who has repeatedly checked in to the plurality of check-in places more than a predetermined number of times during a preset check-in period among users registered in the social network service You can also create
  • a second group may be created by including a user who has checked in at least three times from A to E among the users registered in the social network service as a member of the second group.
  • the members belonging to the first group or the members belonging to the second group may correspond to a user using the item rental service, that is, users subscribed to the item rental service server.
  • the similarity propensity group extractor 230 extracts a similar propensity group for a user based on member information included in each of the plurality of groups.
  • the plurality of groups each include members having at least one association with a user
  • a similar propensity group for recommending rental items is extracted based on the member information of the members included in each of the plurality of groups. can do.
  • At least one member included in all of the plurality of groups may be included in the similar propensity group. That is, a similar propensity group may be generated based on at least one member included in both the first group and the second group.
  • similarity groups may include item rental service users who are frequently in conversation with users on social network services and who are members who visit the same store or place that they have recently visited. Can be.
  • the conversation group in which the members included in the second group among the conversation groups are included in the preset ratio may be extracted as the similar propensity group.
  • the member corresponding to the second group is selected from the plurality of conversation groups extracted to create the first group.
  • a conversation group containing four or more people can be extracted as a similar propensity group.
  • the rental item recommendation unit 240 recommends the rental item to the user based on the rental history of the item rental service for at least one member included in the similar propensity group.
  • the similarity group includes three members A, B, and C.
  • the item rental history for each of A, B, and C is obtained, and the preference information is based on the rental items included in the rental history.
  • the preference information is based on the rental items included in the rental history.
  • the user may recommend at least one item having a history of rental by at least one member included in the similarity group.
  • the rental item to be recommended can be checked whether the user is immediately available for rental, and the user can immediately use the recommended rental items by performing the recommendation only when the property is immediately available for rental.
  • the storage unit 250 stores various information generated in the rental item recommendation process according to an embodiment of the present invention as described above.
  • the storage unit 250 may be configured independently of the rental item recommendation apparatus to support a function for recommending a rental item.
  • the storage 250 may operate as a separate mass storage, and may include a control function for performing the operation.
  • the rental item recommendation device may be equipped with a memory to store information in the device.
  • the memory is a computer readable medium.
  • the memory may be a volatile memory unit, and for other implementations, the memory may be a nonvolatile memory unit.
  • the storage device is a computer readable medium.
  • the storage device may include, for example, a hard disk device, an optical disk device, or some other mass storage device.
  • the user may be able to recommend the appropriate rental item by grasping the preference information of the corresponding user.
  • FIG. 3 is a block diagram illustrating an example of a group generation unit illustrated in FIG. 2.
  • the group generator 220 illustrated in FIG. 2 includes a first group generator 310 and a second group generator 320.
  • the first group generator 310 may generate, as a first group, a conversation group having the largest number of conversations during a preset conversation period among conversation groups registered in the social network service.
  • the conversation groups in which the user conducted the conversation at least once a week from the present time are extracted, and among the extracted conversation groups
  • the conversation group having the largest number of conversations may be created as the first group.
  • the number of conversations may be measured based on the number of messages exchanged with each other.
  • the number of conversations may be measured by checking the occurrence frequency of the conversations by identifying the number of times the conversations started at a specific time point in the conversation group.
  • the user and the members of the conversation group A exchanged 100 messages for 10 minutes at 9 AM on January 1, 2016. Later, we can assume that 200 messages were sent and received again for about 20 minutes at 6 pm on January 1, 2016.
  • the number of conversations is measured based on the number of messages exchanged with each other, the number of conversations of the conversation group A on January 1, 2016 may be measured 300 times.
  • the number of conversations in conversation group A on January 1, 2016, is one conversation at 9 am plus one conversation at 6 pm, totaling 2 Can be measured in times.
  • the criterion for measuring the number of conversations may be used in various ways depending on the system in addition to the above-described method.
  • the second group generator 320 may generate a second group including at least one user who has repeatedly checked in at least a predetermined number of times at a check-in place during a preset check-in period among users registered in the social network service. have.
  • the preset check-in period is one month and the preset reference number is five times
  • the user who has checked in at the check-in place of the user from the current one month before the user registered to the social network service is extracted.
  • a user who has checked in at least five times at a check-in place may be included as a member of the second group.
  • the number of check-in times may be measured in consideration of a time interval in which users registered to the social network service check-in at a check-in place in duplicate.
  • the check-in place C when the check-in place C is located during the movement of the user B, the check-in may be performed several times a day.
  • the wrong user When a second group is generated based on the check-in information, the wrong user may be included as the second group, so a rental item that is not appropriate for the user may be recommended.
  • a check-in time interval may be set in advance, and duplicate check-ins within a set check-in time interval may be ignored. That is, if it is assumed that the check-in time interval is 2 hours, the check-in that occurs repeatedly for the check-in place C until 3 pm after the user B is checked in at the check-in place C at 1 pm may be ignored and not recorded.
  • the check-in time interval may be freely set and changed according to the check-in location or the user.
  • the criterion for measuring the number of check-in may be used in various ways depending on the system in addition to the above-described method.
  • a second group including at least one user who has checked in to the plurality of check-in locations for a preset check-in period among the users registered in the social network service may be created as a member.
  • the preset check-in period is one month and the user has a total of ten check-in locations corresponding to A to J, at least once in each month from A to J among the users registered in the social network service from now to one month ago. May include all checked in users as members of the second group.
  • a second group including as a member at least one user who has repeatedly checked in to the plurality of check-in places more than a predetermined number of times during a preset check-in period among users registered in the social network service You can also create
  • a second group may be created by including a user who has checked in at least three times from A to E among the users registered in the social network service as a member of the second group.
  • the members belonging to the first group or the members belonging to the second group may correspond to a user using the item rental service, that is, users subscribed to the item rental service server.
  • FIG. 4 is a diagram illustrating an item rental service according to an embodiment of the present invention.
  • an item rental service may be provided through a process of user registration, personal offering, delivery, and return or keep. Can be.
  • the user registration process may be subdivided into a membership subscription process and a profiling process.
  • the membership process may correspond to a process in which a user connects to a server and subscribes to use an item rental service.
  • the profiling process may investigate the user's fashion preferences. For example, an item owned by a user may be registered on the server, or an item of a style that the user prefers may be registered on the server.
  • the profiling process by performing a profiling meeting 1: 1 with the user, the user's body shape, fashion shopping occasion, and style can be identified.
  • the personalized offering process may be subdivided into a custom set delivery process, a virtual fitting process, and a pick & confirm process.
  • the custom set delivery process may analyze a user's preference information and then transmit a personal styling set to a mobile application or mail.
  • the personal styling set may be composed of tops, bottoms, shoes, bags, additional items, and the like.
  • the rental item recommendation device may recommend the rental item to the user based on the pay tendency group corresponding to the user.
  • the personal styling set may be provided in a manner of virtual fitting based on the user's body type.
  • the user can confirm the customized set provided through the virtual fitting and confirm only the desired product.
  • the delivery process may package the goods selected in the Pick & Confirm process into a gift box or a dry cleaning type and deliver them to the user's home.
  • the return process uses the rented item for a desired period or a specified period, and then accesses the item rental server and clicks the return button for the item to automatically receive a collection request and return the item. Can be. At this time, after the collection of items for the return button input is completed, the delivery of the next product may be performed.
  • a keep process may be performed based on an item rental server when a user wants to purchase a loaned item.
  • FIG. 5 is a flowchart illustrating a rental item recommendation method using a similar propensity group according to an embodiment of the present invention.
  • the present invention is to provide a technology that can recommend a rental item through the rental history of other users with a similar tendency to the user even when the user first uses the item rental service or the history of renting the item is not sufficient. do.
  • a rental item recommendation method using a similar propensity group generates a plurality of groups related to a user based on a social network service executed through a user terminal. (S510).
  • the social network service may correspond to an online service that establishes a network of connections between acquaintances of the user on the web or people who can share the fields and activities of interest to the user.
  • a social network service may include all kinds of services such as micro blogs, communities, blog messengers, etc., and a member or a user who registers a post based on a user's post, image, or location. It may also mean a service that can communicate with the people.
  • a plurality of groups related to the user may be generated based on posts or groups associated with the user through the social network service.
  • a plurality of groups may be generated in consideration of whether members included in the group have subscribed to the item rental service.
  • an object of the present invention may be to recommend the rental item to a user of a specific terminal by obtaining information of users having similar tendencies with the user of the specific terminal using the service among a plurality of users subscribed to the item rental service. . That is, when creating a plurality of groups, members belonging to each group may have to correspond to users subscribed to the item rental service.
  • the plurality of groups may include a first group selected based on the number of conversations with the user in the social network service usage history of the user and a second group selected based on the check-in place of the user in the social network service usage history. Can be.
  • the first group may be selected from the plurality of groups by checking the number of times of communicating with the user.
  • the second group may be selected using the location information tagged in the post that the user posts as the user's check-in location. have.
  • a second group may be selected based on a place where the user is checked in.
  • the first group and the second group may be selected as one or more than one.
  • the conversation group having the largest number of conversations during the preset conversation period among the conversation groups registered in the social network service may be generated as the first group.
  • the conversation groups in which the user conducted the conversation at least once a week from the present time are extracted, and among the extracted conversation groups
  • the conversation group having the largest number of conversations may be created as the first group.
  • the number of conversations may be measured based on the number of messages exchanged with each other.
  • the number of conversations may be measured by checking the occurrence frequency of the conversations by identifying the number of times the conversations started at a specific time point in the conversation group.
  • the user and the members of the conversation group A exchanged 100 messages for 10 minutes at 9 AM on January 1, 2016. Later, we can assume that 200 messages were sent and received again for about 20 minutes at 6 pm on January 1, 2016.
  • the number of conversations is measured based on the number of messages exchanged with each other, the number of conversations of the conversation group A on January 1, 2016 may be measured 300 times.
  • the number of conversations in conversation group A on January 1, 2016, is one conversation at 9 am plus one conversation at 6 pm, totaling 2 Can be measured in times.
  • the criterion for measuring the number of conversations may be used in various ways depending on the system in addition to the above-described method.
  • a second group including at least one user who has repeatedly checked in at least a predetermined number of times at a check-in place during a preset check-in period may be generated as a member.
  • the preset check-in period is one month and the preset reference number is five times
  • the user who has checked in at the check-in place of the user from the current one month before the user registered to the social network service is extracted.
  • a user who has checked in at least five times at a check-in place may be included as a member of the second group.
  • the number of check-in times may be measured in consideration of a time interval in which users registered to the social network service check-in at a check-in place in duplicate.
  • the check-in place C when the check-in place C is located during the movement of the user B, the check-in may be performed several times a day.
  • the wrong user When a second group is generated based on the check-in information, the wrong user may be included as the second group, so a rental item that is not appropriate for the user may be recommended.
  • a check-in time interval may be set in advance, and duplicate check-ins within a set check-in time interval may be ignored. That is, if it is assumed that the check-in time interval is 2 hours, the check-in that occurs repeatedly for the check-in place C until 3 pm after the user B is checked in at the check-in place C at 1 pm may be ignored and not recorded.
  • the check-in time interval may be freely set and changed according to the check-in location or the user.
  • the criterion for measuring the number of check-in may be used in various ways depending on the system in addition to the above-described method.
  • a second group including at least one user who has checked in to the plurality of check-in locations for a preset check-in period among the users registered in the social network service may be created as a member.
  • the preset check-in period is one month and the user has a total of ten check-in locations corresponding to A to J, at least once in each month from A to J among the users registered in the social network service from now to one month ago. May include all checked in users as members of the second group.
  • a second group including as a member at least one user who has repeatedly checked in to the plurality of check-in places more than a predetermined number of times during a preset check-in period among users registered in the social network service You can also create
  • a second group may be created by including a user who has checked in at least three times from A to E among the users registered in the social network service as a member of the second group.
  • the members belonging to the first group or the members belonging to the second group may correspond to a user using the item rental service, that is, users subscribed to the item rental service server.
  • the rental item recommendation method using the similarity propensity group extracts the similarity propensity group for the user based on the member information included in each of the plurality of groups (S520).
  • the plurality of groups each include members having at least one association with a user
  • a similar propensity group for recommending rental items is extracted based on the member information of the members included in each of the plurality of groups. can do.
  • At least one member included in all of the plurality of groups may be included in the similar propensity group. That is, a similar propensity group may be generated based on at least one member included in both the first group and the second group.
  • similarity groups may include item rental service users who are frequently in conversation with users on social network services and who are members who visit the same store or place that they have recently visited. Can be.
  • the conversation group in which the members included in the second group among the conversation groups are included in the preset ratio may be extracted as the similar propensity group.
  • the member corresponding to the second group is selected from the plurality of conversation groups extracted to create the first group.
  • a conversation group containing four or more people can be extracted as a similar propensity group.
  • the rental item recommendation method using the similarity propensity group recommends the rental item to the user based on the rental history of the item rental service for at least one member included in the similarity propensity group (S530). ).
  • the similarity group includes three members A, B, and C.
  • the item rental history for each of A, B, and C is obtained, and the preference information is based on the rental items included in the rental history.
  • the preference information is based on the rental items included in the rental history.
  • the user may recommend at least one item having a history of rental by at least one member included in the similarity group.
  • the rental item to be recommended can be checked whether the user is immediately available for rental, and the user can immediately use the recommended rental items by performing the recommendation only when the property is immediately available for rental.
  • the rental item recommendation method using a similarity propensity group provides information necessary for the user terminal and item rental service server and rental item recommendation through a network such as a network; Can send and receive
  • a social network usage history for recommending rental items may be received from a user terminal or a social network service server, and recommended item information may be provided to the item rental service server.
  • the user may recommend the appropriate rental item by grasping the preference information of the corresponding user.
  • FIG. 6 is an operation flowchart illustrating an example of a process of extracting a similar propensity group in a rental item recommendation method according to the present invention.
  • a first group may be selected based on the number of conversations with a user in a social network service usage history (S610).
  • the conversation group having the largest number of conversations during the preset conversation period among the conversation groups registered in the social network service may be generated as the first group.
  • the conversation groups in which the user conducted the conversation at least once a week from the present time are extracted, and among the extracted conversation groups
  • the conversation group having the largest number of conversations may be created as the first group.
  • the number of conversations may be measured based on the number of messages exchanged with each other.
  • the number of conversations may be measured by checking the occurrence frequency of the conversations by identifying the number of times the conversations started at a specific time point in the conversation group.
  • the criterion for measuring the number of conversations may be used in various ways depending on the system in addition to the above-described method.
  • the second group may be selected based on the check-in place of the user in the social network service usage history (S620).
  • a second group including at least one user who has repeatedly checked in at least a predetermined number of times at a check-in place during a preset check-in period may be generated as a member.
  • the number of check-in times may be measured in consideration of a time interval in which users registered to the social network service check-in at a check-in place in duplicate.
  • the check-in place C when the check-in place C is located during the movement of the user B, the check-in may be performed several times a day.
  • the wrong user When a second group is generated based on the check-in information, the wrong user may be included as the second group, so a rental item that is not appropriate for the user may be recommended.
  • a check-in time interval may be set in advance, and duplicate check-ins within a set check-in time interval may be ignored. That is, if it is assumed that the check-in time interval is 2 hours, the check-in that occurs repeatedly for the check-in place C until 3 pm after the user B is checked in at the check-in place C at 1 pm may be ignored and not recorded.
  • the check-in time interval may be freely set and changed according to the check-in location or the user.
  • the criterion for measuring the number of check-in may be used in various ways depending on the system in addition to the above-described method.
  • a second group including at least one user who has checked in to the plurality of check-in locations for a preset check-in period among the users registered in the social network service may be created as a member.
  • a second group including as a member at least one user who has repeatedly checked in to the plurality of check-in places more than a predetermined number of times during a preset check-in period among users registered in the social network service You can also create
  • the members belonging to the first group or the members belonging to the second group may correspond to a user using the item rental service, that is, users subscribed to the item rental service server.
  • At least one member included in both the first group and the second group may be included in the similar propensity group to extract the similar propensity group (S630).
  • the plurality of groups each include members having at least one association with a user
  • a similar propensity group for recommending rental items is extracted based on the member information of the members included in each of the plurality of groups. can do.
  • At least one member included in all of the plurality of groups may be included in the similar propensity group. That is, a similar propensity group may be generated based on at least one member included in both the first group and the second group.
  • similarity groups may include item rental service users who are frequently in conversation with users on social network services and who are members who visit the same store or place that they have recently visited. Can be.
  • FIG. 7 is a flowchart illustrating another example of a process of extracting a similar tendency group in the method for recommending rental items according to the present invention.
  • a plurality of conversation groups may be extracted based on a social network service usage history (S710).
  • the second group may be selected based on the check-in place of the user in the social network service usage history (S720).
  • a second group including at least one user who has repeatedly checked in at least a predetermined number of times at a check-in place during a preset check-in period may be generated as a member.
  • the number of check-in times may be measured in consideration of a time interval in which users registered to the social network service check-in at a check-in place in duplicate.
  • the check-in place C when the check-in place C is located during the movement of the user B, the check-in may be performed several times a day.
  • the wrong user When a second group is generated based on the check-in information, the wrong user may be included as the second group, so a rental item that is not appropriate for the user may be recommended.
  • a check-in time interval may be set in advance, and duplicate check-ins within a set check-in time interval may be ignored. That is, if it is assumed that the check-in time interval is 2 hours, the check-in that occurs repeatedly for the check-in place C until 3 pm after the user B is checked in at the check-in place C at 1 pm may be ignored and not recorded.
  • the check-in time interval may be freely set and changed according to the check-in location or the user.
  • the criterion for measuring the number of check-in may be used in various ways depending on the system in addition to the above-described method.
  • a second group including at least one user who has checked in to the plurality of check-in locations for a preset check-in period among the users registered in the social network service may be created as a member.
  • a second group including as a member at least one user who has repeatedly checked in to the plurality of check-in places more than a predetermined number of times during a preset check-in period among users registered in the social network service You can also create
  • the conversation groups included in the second group more than a predetermined ratio among the plurality of conversation groups may be extracted as the similar propensity group.
  • the member corresponding to the second group is selected from the plurality of conversation groups extracted to create the first group.
  • a conversation group containing four or more people can be extracted as a similar propensity group.
  • Computer-readable media suitable for storing computer program instructions and data include, for example, magnetic media such as hard disks, floppy disks, and magnetic tape, such as magnetic disks, compact disk read only memory (CD-ROM), and DVDs.
  • Optical Media such as Digital Video Disk, Magnetic-Optical Media such as Floppy Disk, and Read Only Memory, RAM, Random Semiconductor memories such as access memory (EPM), flash memory, erasable programmable ROM (EPROM), and electrically erasable programmable ROM (EEPROM).
  • the processor and memory can be supplemented by or integrated with special purpose logic circuitry.
  • Examples of program instructions may include high-level language code that can be executed by a computer using an interpreter as well as machine code such as produced by a compiler.
  • Such hardware devices may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.
  • a plurality of groups related to a user are generated based on a social network service executed through a user terminal, and similar propensity groups for the user are extracted based on member information included in each of the plurality of groups.
  • the rental item may be recommended to the user based on the rental history of the item rental service for at least one member included in the propensity group. Furthermore, it is possible to recommend suitable rental items to initial users who have subscribed to the item rental service, thereby improving the profit of the item rental service.

Abstract

L'invention concerne un dispositif permettant de recommander un article de location au moyen d'un groupe de propension similaire et un procédé l'utilisant. Une pluralité de groupes associés à un utilisateur peuvent être générés sur la base d'un service de réseautage social exécuté au moyen d'un terminal utilisateur, un groupe de propension similaire concernant l'utilisateur peut être extrait sur la base d'informations d'éléments comprises dans chacun de la pluralité des groupes, et un article de location peut être recommandé à l'utilisateur sur la base d'un historique de location d'un service de location d'article par rapport à au moins un élément compris dans le groupe de propension similaire. Même lorsqu'un historique de location d'un utilisateur utilisant le service de location d'article n'est pas suffisant, un article de location approprié peut être recommandé au moyen d'une acquisition d'informations de préférence de l'utilisateur concerné.
PCT/KR2017/003313 2016-09-02 2017-03-28 Dispositif de recommandation d'article de location au moyen d'un groupe de propension similaire et procédé d'utilisation associé WO2018043860A1 (fr)

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