JP7370292B2 - Proposed device - Google Patents

Description

The present disclosure relates to a proposed device.

Services using transaction media that mediate electronic commerce between individuals and between individuals and companies are known. In order to encourage the use of such services, Patent Document 1 stores candidate products for sale in association with the user, which are products that the user may put up for sale, and specifies items in an auction system based on the candidate products for sale. The present invention discloses a method for extracting users who are likely to put up a product in a popular product group, or a product that can be substituted for it, and recommending the extracted users to put the product up for sale in an auction system.

International Publication No. 2012/002229

In the system described above, candidate products for sale are products registered by the user using an auction site, and therefore are often a small part of all the user's belongings. Therefore, there are limited opportunities for users to be offered e-commerce transactions such as listings (hereinafter sometimes simply referred to as "transactions"), and even if users have products that are in high demand in the e-commerce market, they cannot make transactions. There was a risk that the proposal would not be made. As a result, there have been insufficient opportunities to encourage users to trade in high-demand products in the electronic commerce market.

The present disclosure describes a proposed device that can increase trading opportunities for high-demand products in the electronic commerce marketplace.

A proposal device according to one aspect of the present disclosure is a proposal device that proposes electronic commerce to a user in a transaction medium that mediates electronic commerce, and includes a first acquisition unit that acquires product information regarding products in electronic commerce; a first estimating unit that estimates high-demand products in e-commerce based on the above information; a second obtaining unit that obtains user information about the user from an information source different from the transaction medium; and a second obtaining unit that estimates the user's belongings based on the user information. a second estimating unit that identifies high-demand belongings that correspond to high-demand items among the belongings; and information for proposing electronic commerce for high-demand belongings to the user. The present invention includes a generation unit that generates proposal information including first information, and an output unit that outputs the proposal information.

This proposed device estimates high-demand products in electronic commerce based on product information. Furthermore, the user's belongings are estimated based on user information obtained from an information source different from a transaction medium that mediates electronic commerce. Then, the user's high-demand belongings corresponding to the high-demand products are identified, proposal information for suggesting electronic commerce for the high-demand belongings to the user is generated, and the proposal information is output. Therefore, for example, even if a user acquires a product from a medium other than a transaction medium that mediates electronic commerce, the product can be presumed to be the user's belongings. According to this configuration, more of the user's belongings can be ascertained, so it is possible to increase the possibility that high-demand belongings will be identified. Therefore, it is possible to increase the possibility that a transaction regarding high-demand belongings corresponding to high-demand products will be proposed to the user. Therefore, according to the proposed device according to one aspect of the present disclosure, it is possible to increase trading opportunities for high-demand products in the electronic commerce market.

According to the present disclosure, it is possible to increase trading opportunities for high-demand products in the electronic commerce market.

FIG. 1 is a schematic configuration diagram of a proposal system including a proposal device according to an embodiment. FIG. 2(a) is a diagram showing an example of basic information. FIG. 2B is a diagram showing an example of position information. FIG. 2C is a diagram showing an example of payment information. FIG. 2(d) is a diagram showing an example of usage information. FIG. 3 is a block diagram showing the functional configuration of the proposed device shown in FIG. 1. FIG. 4 is a diagram illustrating an example of user belongings information. FIG. 5 is a diagram showing an example of high-demand product information. FIG. 6 is a flowchart showing the processing of the belongings estimation method included in the proposal method performed by the proposal device shown in FIG. FIG. 7 is a flowchart showing the process of the proposal information generation method included in the proposal method performed by the proposal device shown in FIG. FIG. 8 is a diagram showing the hardware configuration of the proposed device shown in FIG. 1.

Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In the description of the drawings, the same reference numerals are used for the same or equivalent elements, and overlapping description will be omitted.

The configuration of a proposal system 1 according to an embodiment will be described with reference to FIGS. 1 and 2. FIG. 1 is a schematic configuration diagram of a proposal system 1 including a proposal device 70 according to an embodiment. FIG. 2(a) is a diagram showing an example of basic information. FIG. 2B is a diagram showing an example of position information. FIG. 2C is a diagram showing an example of payment information. FIG. 2(d) is a diagram showing an example of usage information.

A proposal system 1 shown in FIG. 1 is a system that proposes to a user U a transaction in a transaction medium that mediates electronic commerce (hereinafter sometimes simply referred to as a "transaction"). Electronic commerce includes, for example, transactions via so-called flea market apps, transactions via so-called rental apps, and transactions via auction sites. Transaction media that mediate electronic commerce are, for example, electronic commerce sites such as flea market application management sites, rental application management sites, and auction sites.

The outline of how a transaction is proposed to the user U in the proposal system 1 will be briefly described. In proposed system 1, high-demand products that are traded in high demand in the e-commerce market are estimated, and high-demand belongings that correspond to high-demand products among user U's belongings are identified. and a transaction for the high-demand product is proposed to user U. Here, an example will be described in which a specific brand bag X is traded in high demand on an electronic commerce site. It is assumed that user U owns a bag identical to brand bag X (hereinafter referred to as "brand bag X"). In that case, in the proposal system 1, the brand bag X is estimated as a high-demand product, and the belongings of the user U are estimated. User U's belongings include brand bag X. Then, in the proposed system 1, a brand bag X (high-demand belongings) corresponding to the brand bag A listing (electronic commerce) is proposed. As described above, in the proposal system 1, a transaction in a transaction medium that mediates electronic commerce is proposed to the user U.

The proposal system 1 includes one or more terminal devices (terminals) 10, a user information DB 30, one or more external DBs 50, and a proposal device 70. One or more terminal devices 10 are configured to be able to communicate with each other via a network with the user information DB 30 and the proposal device 70. The proposal device 70 is configured to be able to communicate with one or more terminal devices 10, user information DB 30, and external DB 50 via a network. The network may be configured either wired or wireless. Examples of networks include mobile communication networks, the Internet, and WAN (Wide Area Network). Although the following description focuses on one terminal device 10, the same applies to other terminal devices 10.

The terminal device 10 is a device owned by the user U and is a device that the user U can carry. Examples of the terminal device 10 include mobile terminals including smartphones and tablet terminals. The terminal device 10 stores basic information of the user U. Details of the basic information will be described later. The terminal device 10 transmits basic information to the user information DB 30.

The terminal device 10 acquires location information (latitude and longitude) of the terminal device 10 using GPS (Global Positioning System) or the like. The terminal device 10 may obtain information on the installation location of a master station of a connected wireless network as location information. Examples of the installation location of the master station include a base station of a mobile network, a Wi-Fi access point, and the like. The terminal device 10 may acquire location information of a terminal existing in the vicinity of the terminal device 10 as the location information of the terminal device 10. Examples of such terminals include Bluetooth (registered trademark) beacon terminals and the like. Details of the position information will be described later. The terminal device 10 periodically transmits location information to the user information DB 30.

The terminal device 10 generates payment information for the user U. The payment information is information regarding the payment made using the terminal device 10. For example, when user U purchases a product using a payment application installed on terminal device 10, terminal device 10 generates payment information. Details of the payment information will be described later. For example, the terminal device 10 transmits payment information to the user information DB 30 every time payment information is generated.

The terminal device 10 generates usage information for the user U. The usage information is information related to the usage of the application of the terminal device 10 owned by the user U. For example, when user U uses an application on terminal device 10, terminal device 10 generates usage information. Details of the usage information will be described later. The terminal device 10 repeatedly transmits usage information to the user information DB 30, for example, at regular time intervals.

The user information DB 30 is a database that stores user information of each user U. The user information includes user U's basic information, location information, payment information, and usage information.

As shown in (a) of FIG. 2, the basic information of the user U includes the user ID of the user U who uses the terminal device 10, the terminal ID of the terminal device 10 owned by the user U, and the name of the user U. , including user U's gender and user U's place of residence. The user ID is information that can uniquely identify the user U. The terminal ID is information that can uniquely identify the terminal device 10. When receiving basic information from each terminal device 10, the user information DB 30 stores the received basic information. Note that the user information is not limited to the above information, and may be any information related to the user U.

The location information is information indicating the location of the terminal device 10. As shown in FIG. 2B, the location information includes a terminal ID, the time (time stamp) at which the location information was acquired, latitude, and longitude. When receiving position information from each terminal device 10, the user information DB 30 stores the received position information. The user information DB 30 stores a plurality of pieces of position information of each terminal device 10 as a position information history (log).

The payment information is information regarding the payment made by the user U using the terminal device 10. As shown in (c) of FIG. 2, the payment information includes, for example, the terminal ID, the time (time stamp) at which the payment information was acquired, the payment amount, and the product name of the product purchased through the payment. including. When receiving payment information from each terminal device 10, the user information DB 30 stores the received payment information. The user information DB 30 stores a plurality of pieces of payment information for each terminal device 10 as a payment information history (log).

The usage information is information related to the usage of the application of the terminal device 10 owned by the user U. As shown in (d) of FIG. 2, the usage information includes, for example, a terminal ID, a time (time stamp) at which the usage information was acquired, a service (application name), and content. The service is an application used by the user U of the terminal device 10. The content is the content used by the user U among the content provided by the application. An example of a service is a video distribution app. An example of content is an anime video distributed by a video distribution app. When the user information DB 30 receives the usage information from each terminal device 10, the user information DB 30 stores the received usage information. The user information DB 30 stores a plurality of pieces of usage information for each terminal device 10 as a usage information history (log).

The external DB 50 is a database that stores product information. Product information is information regarding products traded in the electronic commerce market, and includes media information. Media information is information regarding products being traded in electronic commerce media. Examples of media information include, on an e-commerce site, the product name and price of each product listed, the product name and price of each product purchased, information about the seller, information about the purchaser, and from listing to purchase. Information such as the period of Further, the product information includes posted information. Posted information is information posted on SNS. Specifically, the posted information is information regarding a posted document posted on the SNS. Examples of posted information include tweets posted by Twitter users on Twitter (registered trademark). Posted information is stored, for example, in an external DB that is different from the external DB in which media information is stored. In each external DB 50, product information is updated every time it is received from an external communication terminal 91, for example.

The proposal device 70 is a device that proposes to the user U a transaction in a transaction medium. An example of the proposed device 70 is an information processing device such as a server device.

The functional configuration of the proposal device 70 will be described with reference to FIG. 3. FIG. 3 is a block diagram showing the functional configuration of the proposal device 70 shown in FIG. 1. As shown in FIG. 3, the proposal device 70 functionally includes an acquisition section 71 (second acquisition section), an estimation section 72 (second estimation section), a storage section 73, and an acquisition section 74 (second estimation section). 1 acquisition section), an estimating section 75 (first estimating section), a specifying section 76 (first specifying section), a determining section 77, a generating section 78, and an output section 79. In the explanation of the proposed method described later, the functions (operations) of each functional section will be explained in detail, so the functions of each functional section will be briefly explained here.

The acquisition unit 71 is a functional unit that acquires user information. The acquisition unit 71 acquires user information from an information source different from the transaction medium. In this embodiment, the acquisition unit 71 acquires user information from the user information DB 30, which is an information source different from the transaction medium. The acquisition unit 71 outputs user information to the estimation unit 72 and the determination unit 77. Note that the acquisition unit 71 may acquire user information from an information source different from the transaction medium, and may acquire user information from a database different from the user information DB 30, for example.

The estimating unit 72 is a functional unit that estimates user U's belongings based on user information. The estimation unit 72 estimates user U's belongings based on the user information received from the acquisition unit 71. In the present embodiment, the estimating unit 72 estimates the belongings of the user U by calculating the possession probability for one or more high-demand product candidates using a belonging estimation model generated using machine learning. do. One or more high-demand product candidates are products that are listed in advance as products that are likely to be in high demand in the future. The following explanation will basically focus on one high-demand product candidate, but the same applies to other high-demand product candidates. The possession probability is the probability that the user U owns the high-demand product candidate. The numerical value of possession probability indicates the possibility that user U has a high-demand product as a possession. A detailed explanation of the method for estimating user U's belongings will be described later. The estimation unit 72 outputs the belongings information to the storage unit 73. The belongings information is information indicating the belongings of the user U, the probability of possession of the belongings, and the like.

The storage unit 73 is a functional unit that stores personal belongings information. As shown in FIG. 4, user U's belongings information includes a user ID, a belongings name, and a possession probability. The property name includes the name of the property, and the name of the vendor such as the brand name and manufacturer name of the property (product), such as "AAA Manga Book Q", for example. The storage unit 73 stores the belongings information received from the estimation unit 72.

The acquisition unit 74 is a functional unit that acquires product information. The acquisition unit 74 acquires product information from the product information stored in the external DB 50. As described above, the product information includes media information and posting information. The acquisition unit 74 outputs product information to the estimation unit 75.

The estimation unit 75 is a functional unit that estimates high-demand products based on product information. High-demand products are products that are traded in high demand in the electronic commerce market. "Transacted in high demand" refers to, for example, a case where there is a large number of listings for a product on an electronic commerce site and a high purchase rate for the product. In this embodiment, "one product" means, for example, the same product sold by the same sales source. In other words, a high-demand product means a product that is the same as a product traded in high demand in the electronic commerce market. Note that "products" are not limited to movable assets, but also include real estate. That is, "product" means various assets owned by user U.

The estimation unit 75 further estimates high-demand transaction media based on the product information. A high-demand trading medium is a trading medium in which high-demand products are traded frequently. "Transactions of high-demand products are carried out frequently" means, for example, that the number of high-demand products listed on an e-commerce site is higher than a predetermined threshold, and that multiple high-demand products are listed for sale on an e-commerce site. This means that the purchase rate for the product is higher than a preset threshold. High demand trading mediums may differ for different high demand products. For example, the high-demand transaction medium for comic book Q, which is a high-demand product, is the first electronic commerce site, and the high-demand transaction medium for brand bag X, which is a high-demand product, is the second electronic commerce site. In this embodiment, the estimation unit 75 estimates high-demand transaction media based on the product information received from the acquisition unit 74.

The estimating unit 75 generates high-demand product information regarding high-demand products, and outputs the generated high-demand product information to the specifying unit 76 and the determining unit 77. The high-demand product information is information indicating high-demand products, high-demand transaction media, and the like.

As shown in FIG. 5, the high-demand product information includes a high-demand product name and a high-demand transaction medium name. The high-demand product name includes the name of the product and the name of the vendor of the product, such as, for example, "AAA Manga Book Q." The region name is information indicating a region where demand for a high-demand product is particularly high.

For example, if Manga Book Q becomes popular in a first region, Manga Book Q may become a high-demand product in the first region, but Manga Book Q may not be a high-demand product in regions other than the first region. be. In that case, the high-demand product information includes comic book Q as the high-demand product name and the first region as the region name. Further, for example, comic book Q may be in high demand at the first electronic commerce site, but may be in low demand at a second electronic commerce site different from the first electronic commerce site. In that case, the high-demand product information includes comic book Q as the high-demand product name and the first electronic commerce site as the high-demand transaction media name.

The identification unit 76 is a functional unit that identifies high-demand belongings. The high-demand belongings are the belongings of the user U that correspond to high-demand products. In this embodiment, "belongings corresponding to a high-demand product" means the same product as the high-demand product. The identifying unit 76 identifies high-demand belongings by comparing the belongings information received from the storage unit 73 and the high-demand product information received from the estimating unit 75. The identifying unit 76 outputs information indicating high-demand belongings to the determining unit 77 and the generating unit 78. Further, the specifying unit 76 outputs the high-demand product information received from the estimating unit 75 to the generating unit 78.

The determining unit 77 is a functional unit that determines whether the user U is using a high-demand transaction medium. In the present embodiment, the determination unit 77 uses the usage information included in the user information received from the acquisition unit 71, the high-demand product information received from the estimation unit 75, and the information indicating high-demand belongings received from the identification unit 76. Based on this, it is determined whether the user U is using a high-demand transaction medium for a high-demand belonging. The determining unit 77 outputs to the generating unit 78 the result of determining whether or not the user U is using a high-demand transaction medium (hereinafter simply referred to as “determination result”).

The generation unit 78 is a functional unit that generates proposal information. In the present embodiment, the generation unit 78 generates proposal information based on the high-demand product information and information indicating high-demand belongings received from the identification unit 76 and the determination result received from the determination unit 77. The generation unit 78 outputs the generated proposal information to the output unit 79.

The output unit 79 is a functional unit that outputs proposal information. The output unit 79 outputs the proposal information received from the generation unit 78 to, for example, the terminal device 10.

Next, a proposal method performed by the proposal device 70 will be described with reference to FIGS. 6 and 7. FIG. 6 is a flowchart showing the processing of the belongings estimation method included in the proposal method performed by the proposal device 70 shown in FIG. FIG. 7 is a flowchart showing the process of the proposal information generation method included in the proposal method performed by the proposal device 70 shown in FIG. The process shown in FIG. 6 is, for example, repeatedly performed at regular time intervals.

As shown in FIG. 6, first, the acquisition unit 71 acquires user information regarding each user U from the user information DB 30 (step S01). Specifically, the acquisition unit 71 acquires the user information of the user U stored in the user information DB 30. The acquisition unit 71 then outputs the user information to the estimation unit 72.

Subsequently, upon receiving the user information from the acquisition unit 71, the estimating unit 72 estimates the belongings of the user U based on the user information (step S02). Specifically, the estimation unit 72 estimates the belongings of the user U based on the user U's basic information, location information, payment information, and usage information included in the user information.

In the present embodiment, the estimation unit 72 estimates the belongings of the user U by calculating the probability of possession of high-demand product candidates using a belonging estimation model generated by machine learning. First, as a premise, one or more products that are likely to be in high demand in the future are listed as one or more high-demand product candidates. In addition, an inventory estimation model is prepared for each high-demand product candidate. The belongings estimation model is generated by being trained in advance using, for example, basic information, location information, payment information, and usage information of a user who owns the same product as the high-demand product candidate. Then, the estimating unit 72 inputs basic information, location information, payment information, and usage information included in the user information as feature amounts to each belongings estimation model for high-demand products. Each belongings estimation model outputs a possession probability that is the probability that the user owns the high-demand product assigned to the belongings estimation model. With this configuration, the estimation unit 72 obtains the possession probability from the belongings estimation model.

Then, the estimating unit 72 estimates, among the high-demand product candidates, a high-demand product candidate that is likely to be owned by the user to be the user's belongings. Specifically, the estimating unit 72 estimates, for example, that a high-demand product candidate whose possession probability is higher than a predetermined threshold is the user's belongings. Then, the estimating unit 72 generates, for each user U, belongings information including the user ID, the name of the belongings of the user U, and the possession probability of the belongings, and outputs the generated belongings information to the storage unit 73. Note that the estimating unit 72 may generate belongings information that further includes the acquisition date on which the belongings are estimated to have been acquired.

Here, a specific example will be described in which the basic information, location information, payment information, and usage information, which are the feature quantities input to the belongings estimation model, can be involved in the possession probability output by the belongings estimation model.

For example, the degree of compatibility between the date of birth included in the basic information and the demand group of a high-demand product candidate may be related to the possession probability. Taking the case where Manga Book Q is a high-demand product candidate as an example, it can be said that the main demand group for Manga Book Q, which is a boy's manga, is people in their teens to 30s. In that case, in the belongings estimation model for the comic book Q, the possession probability may change depending on the relationship between the age of the user U specified from the date of birth and the main demand group for the comic book Q. Specifically, for example, compared to the possession probability (probability of owning comic book Q) when user U is elderly, the possession probability is higher when user U is in his or her teens to 30s. obtain.

For example, the degree of compatibility between the user's movement location estimated based on the timestamp, latitude, and longitude included in the location information and the location where the high-demand product candidate is likely to be sold is determined by the probability of possession. may be involved. Taking Manga Book Q as an example, for example, one of the places where Manga Book Q is most likely to be sold is a convenience store, and user U, who does not usually visit convenience stores, is likely to visit on the release date of Manga Book Q. When the user U visits a convenience store, it is possible that the user U may have purchased the comic book Q. In that case, in the inventory estimation model for comic book Q, the possession probability may be high. However, for example, if the user U moves to multiple convenience stores on the release date, the purpose of the user U moving to the convenience store may be different from purchasing the comic book Q. In that case, in the inventory estimation model for comic book Q, the possession probability may be low.

Furthermore, for example, the degree of compatibility between the product name included in the payment information and the product name of a high-demand product candidate may be related to the possession probability. Taking Manga Book Q as an example, for example, if the product name included in the payment information and the product name of the high-demand product candidate are Manga Book Q, in the inventory estimation model of Manga Book Q, the possession probability will be high. obtain.

Furthermore, for example, if a user U who habitually uses an application is identified based on the service included in the usage information, the behavior of the identified user U who habitually uses the application will affect the possession probability. It is possible. "Using an application habitually" means, for example, continuously using an application at a specific time of day, on a specific day of the week, or the like. Taking the comic book Q as an example, assume that there is a user U who habitually uses applications such as magazines, videos, and games during commuting hours. If user U is not using the application during commuting hours on the release date of comic book Q, there is a possibility that user U has purchased comic book Q and is reading the purchased comic book Q. It can be said. In that case, in the inventory estimation model for comic book Q, the possession probability may be high.

Further, for example, the content of an application that the user U habitually uses may also be involved in the possession probability. Taking Manga Book Q as an example, for example, a user U who habitually uses applications such as animation content videos and anime content games, and a user U who habitually uses magazine applications, , it can be said that there is a possibility that he is in possession of the comic book Q. In that case, in the inventory estimation model for comic book Q, the possession probability may be high.

Subsequently, upon receiving the belongings information (see FIG. 4) from the estimating section 72, the storage section 73 stores the belongings information (step S03). Then, the processing of the belongings estimation method ends.

Next, the processing of the proposal information generation method included in the proposal method (see FIG. 7) will be described. The process shown in FIG. 7 is, for example, repeatedly performed at regular time intervals.

As shown in FIG. 7, first, the acquisition unit 74 acquires product information (step S11). Specifically, the acquisition unit 74 acquires product information stored in the external DB 50. Then, the acquisition unit 74 outputs, for example, product information acquired during the most recent month to the estimation unit 75.

Subsequently, upon receiving the product information from the acquisition unit 74, the estimation unit 75 estimates high-demand products and high-demand transaction media based on the product information (step S12). First, a method for estimating high demand products will be explained. The estimation unit 75 estimates high-demand products based on at least one of medium information and posted information included in the product information. As an example, the estimating unit 75 estimates high-demand products based on media information. Since the method of estimating high demand products using media information is well known, detailed explanation will be omitted.

Furthermore, the estimating unit 75 estimates high-demand products based on posted documents. For example, the estimating unit 75 searches for posted documents that include one product name. Then, the estimating unit 75 estimates that the one product is a high-demand product when the number of posted documents that include the one product name is greater than a predetermined threshold. Alternatively, the estimation unit 75 searches for posted documents that include one product name and a high-demand keyword, and determines whether the number of posted documents that include one product name and a high-demand keyword is less than a predetermined threshold. If there are many products, it is assumed that the product is a high-demand product. High-demand keywords are specific keywords that are assumed to be likely to be used in posts related to high-demand products. Examples of high-demand keywords include "sold out," "out of stock," and "not on sale."

Next, a method for estimating high demand transaction media will be explained. In this embodiment, the estimating unit 75 estimates a high-demand transaction medium based on the medium information included in the product information received from the acquiring unit 74. Specifically, the estimating unit 75 determines that the number of high-demand products exhibited on the e-commerce site is higher than a predetermined threshold, and the purchase rate for the plurality of high-demand products exhibited is higher than a predetermined threshold. is also high, it is assumed that the e-commerce site is a high-demand transaction medium.

Then, the estimating unit 75 generates high-demand product information including the high-demand product name and the high-demand transaction medium name, and outputs the generated high-demand product information to the specifying unit 76 and the determining unit 77.

Subsequently, the identifying unit 76 identifies high-demand belongings that correspond to high-demand products among user U's belongings based on the belongings information and high-demand product information (step S13). In step S13, first, the identification unit 76 acquires the belongings information of each user U from the storage unit 73. Note that the identifying unit 76 may acquire the belongings information of the user U who satisfies a predetermined condition among each user. Although the following explanation focuses on one user U, the same applies to other users U.

Next, the identifying unit 76 receives high-demand product information from the estimating unit 75. Then, the identifying unit 76 identifies high-demand belongings by comparing the belongings information with the high-demand product information. In the present embodiment, the identification unit 76 identifies a personal item having the same personal item name as a high-demand product name as a personal item corresponding to a high-demand product. Specifically, when the name and vendor of the product included in the high-demand product name match the name and vendor of the property (product) included in the property name, the identification unit 76 identifies the property. are identified as high-demand possessions. Through the above processing, the identification unit 76 identifies the high-demand belongings of the user U. The identifying unit 76 then outputs information indicating the identified high-demand belongings to the determining unit 77 and the generating unit 78. Further, the specifying unit 76 outputs the high-demand product information received from the estimating unit 75 to the generating unit 78.

Subsequently, the determining unit 77 determines whether the user U is using a high-demand transaction medium (step S14). In the present embodiment, the determination unit 77 uses the usage information included in the user information received from the acquisition unit 71, the high-demand product information received from the estimation unit 75, and the information indicating high-demand belongings received from the identification unit 76. Based on this, it is determined whether the user U is using a high-demand transaction medium. Specifically, the determining unit 77 determines whether an application of a high-demand transaction medium for a high-demand belonging is included in the service (application name) included in the usage information.

If the application of the high-demand transaction medium for the high-demand product is included in the services included in the usage information, the determination unit 77 determines that the user U is using the high-demand transaction medium (step S14: YES). ), outputs to the generation unit 78 a determination result indicating that user U is using a high-demand transaction medium. On the other hand, if the application of the high-demand transaction medium is not included in the services included in the usage information, the determination unit 77 determines that the user U is not using the high-demand transaction medium (step S14: NO), A determination result indicating that the user U is not using the high-demand transaction medium is output to the generation unit 78.

Subsequently, the generation unit 78 receives high-demand product information and information indicating high-demand belongings from the identification unit 76, and upon receiving the determination result from the determination unit 77, generates proposal information (steps S15, S16). In this embodiment, the generation unit 78 generates proposal information according to the result of the determination by the determination unit 77 as to whether or not the user U is using a high-demand transaction medium. The proposal information generated by the generation unit 78 will be described in detail below.

If the determining unit 77 determines that the user U is using a high-demand transaction medium (step S14: YES), the generating unit 78 generates proposal information including the first information and the second information (step S15). ). The first information is information for proposing to user U a transaction of high-demand belongings. In the present embodiment, the first information is information indicating that a transaction of high-demand belongings is proposed to the user U. The second information is information indicating a high demand transaction medium. The generation unit 78 generates first information based on the information indicating the high-demand belongings received from the identification unit 76 . Furthermore, the generation unit 78 generates second information based on information indicating a high-demand transaction medium included in the high-demand product information received from the identification unit 76 . The generation unit 78 then outputs the generated proposal information to the output unit 79.

On the other hand, if the determining unit 77 determines that the user U is not using the high-demand transaction medium (step S14: NO), the generating unit 78 generates proposal information including the first information, the second information, and the third information. is generated (step S16). The third information is information for recommending the use of high-demand transaction media. The generation unit 78 generates third information based on the information indicating the high-demand transaction medium included in the high-demand product information received from the identification unit 76 and the determination result received from the determination unit 77. The generation unit 78 then outputs the generated proposal information to the output unit 79.

Here, regarding the proposal information generated by the generation unit 78, the comic book Q owned by the user U is traded in high demand on the first e-commerce site, and the user U uses the first e-commerce site This will be explained using an example that is not used. In that case, the estimating unit 72 estimates the comic book Q as a property of the user U, and the estimating unit 75 estimates the comic book Q as a high-demand product and the first e-commerce site as a high-demand transaction medium. . Then, the identifying unit 76 identifies the comic book Q among the user U's belongings as a high-demand belonging corresponding to a high-demand product, and the determining unit 77 selects the first e-commerce site (high-demand transaction medium). It is determined that user U is not using it. In that case, the generation unit 78 generates proposal information including the following first information, second information, and third information.

The first information is information that proposes trading of comic book Q (high demand product) to user U. The second information is information indicating that the first electronic commerce site is a high-demand transaction medium. The third information is information indicating that the use of the first electronic commerce site (high demand transaction medium) is recommended. The generation unit 78 outputs proposal information including the first information, second information, and third information as described above to the output unit 79.

Subsequently, upon receiving the proposal information from the generation section 78, the output section 79 outputs the proposal information (step S17). In this embodiment, upon receiving the proposal information from the generation section 78, the output section 79 transmits the proposal information to the terminal device 10. Then, the proposal information generation process ends.

The proposal device 70 described above estimates high-demand products in transactions based on product information. Furthermore, user U's belongings are estimated based on user information acquired from an information source (user information DB 30) different from the transaction medium that mediates the transaction. Then, the high-demand belongings of the user U corresponding to the high-demand products are identified, proposal information for suggesting a transaction of the high-demand belongings to the user U is generated, and the proposal information is output. Therefore, for example, even if user U acquires a product from a medium other than the transaction medium that mediates the transaction, the product can be presumed to be user U's belongings. According to this configuration, more of the belongings of the user U can be ascertained, so it is possible to increase the possibility that high-demand belongings will be identified. Therefore, it is possible to increase the possibility that a transaction regarding high-demand belongings corresponding to high-demand products will be proposed to user U. Therefore, according to the proposed device 70, it is possible to increase the opportunities for trading high-demand products in the electronic commerce market.

In the proposed device 70, the user information includes user U's basic information, user U's location information, and user U's usage information. From the basic information of user U, for example, the degree of compatibility between user U and the demand group for high-demand products can be estimated. Further, from the position information of the user U, for example, the product acquisition behavior of the user U in the real world can be estimated. Further, from the usage information, for example, user U's product acquisition behavior on the Internet can be estimated. Since user information including such information is used to estimate user U's belongings, the proposal device 70 makes it possible to estimate user U's belongings with high accuracy.

The product information includes posted information posted on external SNS, and the estimation unit 75 estimates high-demand products based on the posted information. Posted information is information acquired in real time. Therefore, for example, even if the demand for a product suddenly increases due to current events, it can be quickly estimated that the product is a high-demand product based on information acquired in real time. As a result, prompt transactions of high-demand products can be encouraged.

The estimation unit 75 further specifies the high-demand transaction medium, and the proposal information further includes second information that is information indicating the high-demand transaction medium. For example, there are cases where the demand for one product is high in a certain trading medium, while the demand for that one product is low in another trading medium. In other words, the degree of demand for a product may vary depending on the transaction medium. In the proposal device 70, since the user U can grasp the media in which high-demand products corresponding to the belongings are frequently traded, the user U's desire to trade high-demand products (high-demand belongings) is increased. be able to.

The determination unit 77 determines whether the user U is using a high-demand transaction medium, and the generation unit 78 determines whether the determination unit 77 determines whether the user U is using a high-demand transaction medium. Generate suggestion information according to the results.

For example, it is assumed that the user U who has already used a high-demand transaction medium is likely to be motivated to trade high-demand belongings using the high-demand transaction medium. On the other hand, it is assumed that the user U who does not use a high-demand transaction medium is hard to feel motivated to trade high-demand belongings using a high-demand transaction medium. Since the proposal device 70 outputs proposal information according to the usage status of the high-demand transaction medium by the user U, it is possible to further increase the user U's desire to trade high-demand products (high-demand belongings).

In particular, in the proposal device 70, the generation unit 78 generates information indicating that the use of a high-demand transaction medium is recommended when the determination unit 77 determines that the user U is not using a high-demand transaction medium. Proposal information further including third information is generated.

For example, even if a user U who does not use a high-demand transaction medium is notified that high-demand belongings are frequently traded in the high-demand transaction medium, the user U does not use the high-demand transaction medium. It is assumed that compared to users who are already using the service, it is difficult to feel motivated to engage in the transaction. The proposal device 70 simultaneously presents information for trading high-demand belongings and information recommending the use of high-demand transaction media to the user U who does not use high-demand transaction media. User U's desire to trade in-demand products (high-demand belongings) can be further increased.

Although the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above embodiments.

The high-demand product may be, for example, a product in the same category as a product traded in high demand in an electronic commerce market. In that case, the estimating unit 75 first estimates the category of the product traded in high demand, and then estimates the product belonging to the category as the high-demand product. For example, assume that curing tape is traded in high demand in the electronic commerce market, regardless of the vendor. In that case, the estimating unit 75 estimates curing tape as a category of products traded in high demand, and estimates a product (curing tape) belonging to this category as a high-demand product.

The estimation unit 75 does not need to estimate the high-demand transaction medium in the process of step S13. In that case, the proposal information does not include the second information. Further, the proposal device 70 does not need to include the determination unit 77. In that case, the proposal information does not include the third information. Furthermore, the generation unit 78 may generate proposal information that includes only the first information. The first information may be information for suggesting a transaction of a high-demand belonging to the user U, and may be, for example, information indicating a high-demand product. Furthermore, the generation unit 78 may generate proposal information that does not include the third information even if the determination unit 77 determines that the user U is not using the high-demand transaction medium in step S16. .

The identifying unit 76 may identify the high-demand belongings by considering the probability of possession of the user U's belongings. As an example, the identifying unit 76 identifies an item having the same item name as a high-demand product name, and the probability of possession of the item is higher than a predetermined threshold (hereinafter referred to as "first threshold"). identify the item as a high-demand item if the item is a high-demand item. Note that the first threshold value is set higher than the threshold value (hereinafter referred to as "second threshold value") used for estimating the belongings estimated by the estimation unit 72.

The estimation unit 75 may further estimate the demand amount and supply amount of the high-demand product based on the product information. The high-demand product information may further include demand quantity and supply quantity. In that case, in the above modification example in which the high-demand belongings are identified by considering the possession probability, the identifying unit 76 may identify the high-demand belongings by further considering the demand amount and the supply amount.

The demand quantity is a value indicating the degree of demand for a high-demand product in the electronic commerce market. The supply amount is a value indicating the degree of supply of a high-demand product in the electronic commerce market. As an example, the estimating unit 75 specifies the demand amount and the supply amount based on the medium information, and outputs high-demand product information including the demand amount and the supply amount to the specifying unit 76. Then, the specifying unit 76 determines whether the balance value, which is the value obtained by subtracting the supply amount from the demand amount, is higher than the third threshold value. The balance value is a value indicating the degree of balance between supply and demand for high-demand products in the electronic commerce market. The closer the balance value is to 0, the more appropriate the balance between demand and supply is. The third threshold is the maximum allowable balance value.

If it is determined that the balance value is higher than the third threshold, the specifying unit 76 determines that the supply of the high-demand product is insufficient, and lowers the first threshold according to the degree of the shortage of supply of the high-demand product. The identifying unit 76 then identifies the high-demand belongings described above. In other words, in the proposal device 70 of this modification, when the supply of high-demand products is insufficient to meet the demand for the high-demand products, more high-demand product candidates are estimated as the user U's belongings, and then the high-demand products Identify.

According to the above modification, for example, when the demand for a high-demand product is low, the number of transactions proposed to user U is reduced, and when the demand for a high-demand product is high, the number of transactions proposed to user U is reduced. Since the number of transaction proposals increases, it becomes possible to adjust the number of high-demand belongings exhibited in the electronic commerce market. Therefore, the balance between demand and supply of high-demand products can be maintained.

The generation unit 78 may generate proposal information when the determination unit 77 determines that the user U is using a high-demand transaction medium. In that case, the output unit 79 outputs the proposal information to the terminal device 10 of the user U who is using the high-demand transaction medium. It can generally be said that a user U who has already used a transaction medium is more likely to conduct a transaction for his/her belongings than a user who has never used a transaction medium. In the proposal device 70 of this modification, in order to propose a transaction to a user U who is using a transaction medium in which a high-demand product is already traded (that is, a user U who can easily conduct a transaction in a high-demand product), It is possible to increase the possibility of efficiently proposing a transaction to the user U regarding the in-demand belongings.

Although the estimating unit 75 estimated high-demand products based on the media information and posted information included in the product information, the estimating unit 75 may estimate high-demand products based only on posted information, Alternatively, high-demand products may be estimated based on information different from media information and posted information. Further, although the estimating unit 75 estimated the high-demand transaction medium based on the media information included in the product information, the estimating unit 75 may also estimate the high-demand transaction medium based on information different from the media information. good.

The proposed device 70 may be configured by one device that is physically or logically coupled, or may be configured by a plurality of devices that are physically or logically separated from each other. For example, the proposed device 70 may be realized by a plurality of computers distributed over a network such as cloud computing. As described above, the configuration of the proposal device 70 may include any configuration that can realize the functions of the proposal device 70.

It should be noted that the block diagram used in the description of the above embodiment shows blocks in functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using one physically or logically coupled device, or may be realized using two or more physically or logically separated devices directly or indirectly (e.g. , wired, wireless, etc.) and may be realized using a plurality of these devices. The functional block may be realized by combining software with the one device or the plurality of devices.

Functions include judgment, decision, judgment, calculation, calculation, processing, derivation, investigation, exploration, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, These include broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assigning. It is not limited to functions. For example, a functional block (configuration unit) that performs transmission is called a transmitting unit or transmitter. In either case, as described above, the implementation method is not particularly limited.

For example, the proposal device 70 in an embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure. FIG. 8 is a diagram illustrating an example of the hardware configuration of the proposal device 70 according to an embodiment of the present disclosure. The proposed device 70 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, and the like.

Note that in the following description, the word "apparatus" can be read as a circuit, a device, a unit, etc. The hardware configuration of the proposed device 70 may be configured to include one or more of each device shown in the figure, or may be configured not to include some of the devices.

Each function in the proposed device 70 is implemented by loading predetermined software (programs) onto hardware such as the processor 1001 and the memory 1002, so that the processor 1001 performs calculations, controls communication by the communication device 1004, and controls the memory 1002. This is realized by controlling at least one of data reading and writing in the storage 1003.

The processor 1001, for example, operates an operating system to control the entire computer. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic device, a register, and the like. For example, each function of the proposal device 70 described above may be realized by the processor 1001.

Furthermore, the processor 1001 reads programs (program codes), software modules, data, and the like from at least one of the storage 1003 and the communication device 1004 to the memory 1002, and executes various processes in accordance with these. As the program, a program that causes a computer to execute at least part of the operations described in the above embodiments is used. For example, each function of the proposed device 70 may be realized by a control program stored in the memory 1002 and operated on the processor 1001. Although the various processes described above have been described as being executed by one processor 1001, they may be executed by two or more processors 1001 simultaneously or sequentially. Processor 1001 may be implemented by one or more chips. Note that the program may be transmitted from a network via a telecommunications line.

The memory 1002 is a computer-readable recording medium, and includes at least one of ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. may be done. Memory 1002 may be called a register, cache, main memory (main memory), or the like. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing the proposed method according to an embodiment of the present disclosure.

The storage 1003 is a computer-readable recording medium, such as an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (such as a compact disk, a digital versatile disk, or a Blu-ray disk). (registered trademark disk), smart card, flash memory (eg, card, stick, key drive), floppy disk, magnetic strip, etc. Storage 1003 may also be called an auxiliary storage device. The storage medium mentioned above may be, for example, a database including at least one of memory 1002 and storage 1003, a server, or other suitable medium.

The communication device 1004 is hardware (transmission/reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, or the like. The communication device 1004 includes, for example, a high frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). It may be composed of. For example, the above-described acquisition units 71 and 74, output unit 79, etc. may be realized by the communication device 1004.

The input device 1005 is an input device (eg, keyboard, mouse, microphone, switch, button, sensor, etc.) that accepts input from the outside. The output device 1006 is an output device (for example, a display, a speaker, an LED lamp, etc.) that performs output to the outside. Note that the input device 1005 and the output device 1006 may have an integrated configuration (for example, a touch panel).

Further, each device such as the processor 1001 and the memory 1002 is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses for each device.

Further, the proposed device 70 includes hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), and a field programmable gate array (FPGA). A part or all of each functional block may be realized by the hardware. For example, processor 1001 may be implemented using at least one of these hardwares.

Notification of information is not limited to the aspects/embodiments described in this disclosure, and may be performed using other methods.

The processing procedures, sequences, flowcharts, etc. of each aspect/embodiment described in this disclosure may be rearranged in order as long as there is no contradiction. For example, the methods described in this disclosure use an exemplary order to present elements of the various steps and are not limited to the particular order presented.

Information etc. can be output from an upper layer (or lower layer) to a lower layer (or upper layer). Information etc. may be input/output via multiple network nodes.

The input/output information may be stored in a specific location (for example, memory) or may be managed using a management table. Information etc. to be input/output may be overwritten, updated, or additionally written. The output information etc. may be deleted. The input information etc. may be transmitted to other devices.

Judgment may be made using a value expressed by 1 bit (0 or 1), a truth value (Boolean: true or false), or a comparison of numerical values (for example, a predetermined value). (comparison with a value).

Each aspect/embodiment described in this disclosure may be used alone, may be used in combination, or may be switched and used in accordance with execution. Further, notification of prescribed information (for example, notification of “X”) is not limited to explicit notification, but may also be done implicitly (for example, by not notifying the prescribed information). Good too.

Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described in this disclosure. The present disclosure can be implemented as modifications and changes without departing from the spirit and scope of the present disclosure as determined by the claims. Therefore, the description of the present disclosure is for illustrative purposes only and is not meant to be limiting on the present disclosure.

Software includes instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, whether referred to as software, firmware, middleware, microcode, hardware description language, or by any other name. , should be broadly construed to mean an application, software application, software package, routine, subroutine, object, executable, thread of execution, procedure, function, etc.

Additionally, software, instructions, information, etc. may be sent and received via a transmission medium. For example, if the software uses wired technology (coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), etc.) and/or wireless technology (infrared, microwave, etc.) to When transmitted from a server or other remote source, these wired and/or wireless technologies are included within the definition of transmission medium.

The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may refer to voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or May be represented by any combination.

Note that terms explained in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings.

As used in this disclosure, the terms "system" and "network" are used interchangeably.

Further, the information, parameters, etc. described in this disclosure may be expressed using absolute values, relative values from a predetermined value, or other corresponding information. It may also be expressed as

The names used for the parameters mentioned above are not restrictive in any respect. Furthermore, the mathematical formulas etc. using these parameters may differ from those explicitly disclosed in this disclosure.

As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of operations. "Judgment" and "decision" include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, search, and inquiry. (e.g., searching in a table, database, or other data structure), ascertaining something as a "judgment" or "decision," etc. In addition, "judgment" and "decision" refer to receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, and access. (accessing) (for example, accessing data in memory) may include considering something as a "judgment" or "decision." In addition, "judgment" and "decision" refer to resolving, selecting, choosing, establishing, comparing, etc. as "judging" and "determining". may be included. In other words, "judgment" and "decision" may include regarding some action as having been "judged" or "determined." Further, "judgment (decision)" may be replaced with "assuming", "expecting", "considering", or the like.

The terms "connected", "coupled", or any variations thereof, mean any connection or coupling, direct or indirect, between two or more elements and each other. It may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled." The bonds or connections between elements may be physical, logical, or a combination thereof. For example, "connection" may be replaced with "access." As used in this disclosure, two elements may include one or more wires, cables, and/or printed electrical connections, as well as in the radio frequency domain, as some non-limiting and non-inclusive examples. , electromagnetic energy having wavelengths in the microwave and optical (both visible and non-visible) ranges, and the like.

As used in this disclosure, the phrase "based on" does not mean "based solely on" unless explicitly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

As used in this disclosure, any reference to elements using the designations "first," "second," etc. does not generally limit the amount or order of those elements. These designations may be used in this disclosure as a convenient way to distinguish between two or more elements. Thus, reference to a first and second element does not imply that only two elements may be employed or that the first element must precede the second element in any way.

The "unit" in the configuration of each of the above devices may be replaced with "circuit", "device", or the like.

Where the terms "include", "including", and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising". Something is intended. Furthermore, the term "or" as used in this disclosure is not intended to be exclusive or.

In this disclosure, when articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are plural.

In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." Note that the term may also mean that "A and B are each different from C". Terms such as "separate" and "coupled" may also be interpreted similarly to "different."

70... Proposed device, 71... Acquisition unit (second acquisition unit), 72... Estimation unit (second estimation unit), 74... Acquisition unit (first acquisition unit), 75... Estimation unit (first estimation unit), 76 ... Specification section (first specification section), 77 ... Determination section, 78 ... Generation section, 79 ... Output section, U ... User, X ... Brand bag (high demand product, high demand belongings).

Claims (6)

A proposal device that proposes electronic commerce to a user in a transaction medium that mediates electronic commerce, comprising:
a first acquisition unit that acquires product information regarding products in electronic commerce;
a first estimation unit that estimates a high-demand product in electronic commerce and a high-demand transaction medium that is a transaction medium in which electronic commerce of the high-demand product is frequently conducted, based on the product information;
a second acquisition unit that acquires user information about the user from an information source different from the transaction medium;
a second estimation unit that estimates the user's belongings based on the user information;
a first identifying part that identifies high-demand belongings that correspond to the high-demand products among the belongings;
a generating unit that generates proposal information including first information that is information for proposing electronic commerce of the high-demand belongings to the user and second information that is information indicating the high-demand transaction medium ;
an output unit that outputs the proposal information;
A proposed device comprising: The proposing device according to claim 1, wherein the user information includes at least one of basic information about the user, location information about the user, and information regarding use of an application on a terminal owned by the user. The product information includes posted information posted on external SNS,
The proposal device according to claim 1 or 2, wherein the first estimation unit estimates the high-demand product based on the posted information. further comprising a determination unit that determines whether the user is using the high-demand transaction medium,
Any one of claims 1 to 3, wherein the generating unit generates the proposal information according to a result of determining whether or not the user uses the high-demand transaction medium in the determining unit. The proposed device described in Section . The proposal device according to claim 4 , wherein the generation unit generates the proposal information when the determination unit determines that the user is using the high-demand transaction medium. The generation unit further generates third information that is information indicating that use of the high-demand transaction medium is recommended when the determination unit determines that the user is not using the high-demand transaction medium. The proposal device according to claim 4 or 5 , which generates the proposal information including the proposal information.

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