Information processing device, information processing method, and information processing program

Abstract

To assist in inferring plausible attributes about a user. [Solution] The information processing device according to the present application has an acquisition unit and an estimation unit. The acquisition unit acquires usage history information of an electronic payment service provided via a terminal device used by a service user of the electronic payment service. The estimation unit estimates attribute information indicating attributes of the service user based on the usage history information acquired by the acquisition unit.

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] Conventionally, there have been proposed techniques for estimating various pieces of information about a user using information acquired from a terminal device used by the user. In relation to such techniques, for example, there has been proposed a technique for estimating attribute information of a user using detection information detected by a terminal device moving with the user. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-68044 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above conventional techniques leave room for improvement in supporting the estimation of plausible attributes for a user.

[0005] The present application has been made in consideration of the above, and has an object to provide an information processing device, an information processing method, and an information processing program capable of assisting in estimating plausible attributes of a user. [Means for solving the problem]

[0006] The information processing device according to the present application includes an acquisition unit and an estimation unit. The acquisition unit acquires usage history information of an electronic payment service provided via a terminal device used by a service user of the electronic payment service. The estimation unit estimates attribute information indicating attributes of the service user based on the usage history information acquired by the acquisition unit. Effect of the Invention

[0007] According to one aspect of the embodiment, it is possible to provide an effect of assisting in estimating plausible attributes of a user. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an information processing system according to an embodiment. [Diagram 2] FIG. 2 is a diagram for explaining an overview of information processing according to the embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an overview of the usage history information according to the embodiment. [Diagram 5] FIG. 5 is a flowchart illustrating an example of a processing procedure of information processing executed by the information processing device according to the embodiment. [Figure 6] FIG. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device according to the embodiment or the modification. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the information processing device, the information processing method, and the information processing program according to the present application (hereinafter, referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program are not limited to the embodiments. In addition, the same components in the following embodiments are given the same reference numerals, and duplicated descriptions will be omitted.

[0010] [Embodiment] (1-1. System Configuration) Hereinafter, the configuration of the information processing system SYS according to the embodiment will be described with reference to the drawings. Fig. 1 is a diagram showing an example of the configuration of the information processing system according to the embodiment.

[0011] As shown in Fig. 1, the information processing system SYS according to the embodiment is configured to include multiple terminal devices 10, a payment service providing device 20, an operator device 30, and an information processing device 100. Note that the configuration of the information processing system SYS shown in Fig. 1 is an example, and may include other devices other than those exemplified in Fig. 1.

[0012] Terminal device 10, payment service providing device 20, operator device 30, and information processing device 100 are connected to network N by wire or wirelessly. Terminal device 10, payment service providing device 20, operator device 30, and information processing device 100 can communicate with other devices via network N.

[0013] The network N includes, for example, a wide area network (WAN) such as the Internet, and mobile communication networks such as long term evolution (LTE), 4th generation (4G), and 5th generation (5G: fifth generation mobile communication system).

[0014] Terminal device 10 is connected to network N by short-range wireless communication such as a mobile communication network, Bluetooth (registered trademark), or wireless LAN (Local Area Network), and can communicate with other devices such as payment service providing device 20 through network N.

[0015] Furthermore, terminal device 10 is used by user U, who is a service user of the electronic payment service provided by payment service providing device 20. Each of the multiple terminal devices 10 is used by a different user U.

[0016] The terminal device 10 may be, for example, a notebook PC (Personal Computer), a desktop PC, a smartphone, a tablet PC, or a wearable device. Examples of the wearable device include, but are not limited to, smart glasses and a smart watch.

[0017] A user U of terminal device 10 can use a payment application program (hereinafter referred to as a "payment app") pre-installed in terminal device 10 in order to use an electronic payment service. User U operates terminal device 10 to launch the payment app, and can use various functions installed in the payment app to execute various processes related to the electronic payment service in cooperation with payment service providing device 20. For example, terminal device 10 can display web content provided by payment service providing device 20 using the payment app. When terminal device 10 receives control information for implementing information display processing from payment service providing device 20, it implements the display processing in accordance with the control information.

[0018] Furthermore, when terminal device 10 receives control information for implementing predetermined information processing from payment service providing device 20, it implements the information processing in accordance with the control information. Here, the control information is described, for example, in a script language such as JavaScript (registered trademark), a style sheet language such as CSS (Cascading Style Sheets), a programming language such as Java (registered trademark), or a markup language such as HTML (HyperText Markup Language). Note that a predetermined application distributed from payment service providing device 20 or the like may itself be regarded as control information.

[0019] Payment service providing device 20 executes various processes related to the electronic payment service. Payment service providing device 20 is operated and managed by a service provider that provides electronic payment services. When payment service providing device 20 is configured as a server device, it may be realized by a single server device, or may be realized by a cloud system in which multiple server devices and multiple storage devices operate in cooperation with each other.

[0020] The payment service providing device 20 can provide the user U with an environment for realizing code payment executed using the terminal device 10 through the electronic payment service. Code payment executed using the terminal device 10 is also called "smartphone payment" when the terminal device 10 is a smartphone.

[0021] Payment service providing device 20 manages, for example, providers of transaction objects provided to user U, and electronic money accounts (also referred to as "electronic wallets") of user U to which transaction objects are provided. Payment service providing device 20 can realize smartphone payments by transferring electronic money between accounts in accordance with payment requests from service users accepted through a payment app. Note that electronic money may be, for example, points or currencies used independently by various companies, or may be electronically tradable currencies provided by countries, such as Japanese yen or dollars.

[0022] The operator device 30 is used by an operator OP who analyzes various information related to a user U. The operator device 30 is, for example, a notebook PC (Personal Computer), a desktop PC, a smartphone, a tablet PC, or a wearable device. Examples of wearable devices include, but are not limited to, smart glasses and smart watches.

[0023] The information processing device 100 executes information processing according to the embodiment described below. When the information processing device 100 is configured as a server device, it may be realized by a single server device, or may be realized by a cloud system in which multiple server devices and multiple storage devices operate in cooperation with each other. The information processing device 100 is an example of an information processing device that realizes the information processing method according to the present application.

[0024] (1-2. Payment using terminal device 10) An example of a code payment process executed using the terminal device 10 will be described below. In the following description, for example, a two-dimensional code (QR code (registered trademark)) placed in a specific store and indicating store identification information for identifying the specific store is used to perform a payment using the terminal device 10 by a user U who receives a transaction object from a specific store. Note that the example of code payment described below is also applicable to a case where an arbitrary user uses an arbitrary terminal device 10 to perform a payment at an arbitrary store. In addition, the two-dimensional code indicating the store identification information may be not only a QR code, but also a barcode, a predetermined mark, a number, or the like. In addition, the two-dimensional code is not limited to an example physically formed by a printed matter printed on a medium such as paper, and may be formed by image information displayed on an arbitrary terminal.

[0025] For example, when user U makes a payment for the purchase or use of a transaction object such as various products or services at a specific store, user U starts a payment app pre-installed in terminal device 10 to use code payment. User U can use various functions related to code payment through the payment app. User U then photographs a two-dimensional code installed at the specific store through the payment app. In such a case, terminal device 10 displays a screen for inputting the price of the transaction object, and accepts input of the payment amount from user U or a clerk at the specific store. Then, terminal device 10 transmits transaction information including user identification information for identifying user U, store identification information (or information indicated by the store identification information, i.e., information indicating the specific store (for example, store ID)), and the payment amount to payment service providing device 20 (for example, see FIG. 1).

[0026] When the payment service providing device 20 accepts the transaction information from the terminal device 10, it transfers electronic money equivalent to the payment amount from the account of the user U indicated by the user identification information to the account of the specified store indicated by the store identification information. At this time, the payment service providing device 20 may transfer the electronic money to the account of the specified store after subtracting a predetermined fee to be charged to the specified store from the electronic money equivalent to the payment amount. Then, the payment service providing device 20 transmits a notification that the transaction has been completed to the terminal device 10. In such a case, the terminal device 10 notifies the user U that the electronic money transaction has been completed by outputting a screen or a predetermined sound indicating that the transaction has been completed. Alternatively, the payment service providing device 20 may withdraw electronic money equivalent to the payment amount from the account of the user U indicated by the user identification information, manage it as sales information of the specified store, and transfer cash equivalent to the sales at a predetermined timing to a bank account held by the specified store. In this case, payment service providing device 20 may notify user U that the transaction using electronic money has been completed at the time that electronic money equivalent to the payment amount has been withdrawn from user U's account.

[0027] It should be noted that the payment using the terminal device 10 is not limited to the above-mentioned process. For example, the payment using the terminal device 10 may be made using a device installed in a specific store (hereinafter referred to as a "store terminal"). Specifically, the terminal device 10 first displays code information indicating user identification information for identifying the user U on a screen. In such a case, the store terminal reads the user identification information from the code information displayed on the terminal device 10, and transmits transaction information including the read user identification information (or information indicated by the user identification information, i.e., information indicating the user U (e.g., user ID)), the payment amount, and information identifying the specific store to the payment service providing device 20.

[0028] When the payment service providing device 20 receives the transaction information from the store terminal, it transfers electronic money equivalent to the payment amount from the account of the user U indicated by the user identification information to the account of the specified store. Then, the payment service providing device 20 transmits a notification that the transaction has been completed to the store terminal or the terminal device 10. The store terminal or the terminal device 10 notifies the user U that the electronic money transaction has been completed by outputting a screen or a specified sound indicating that the transaction has been completed. The payment service providing device 20 may also withdraw electronic money equivalent to the payment amount from the account of the user U indicated by the user identification information, manage the electronic money as sales information of the specified store, and transfer cash equivalent to the sales amount to a bank account held by the specified store at a specified timing. In this case, the payment service providing device 20 may notify the store clerk or the user U that the electronic money transaction has been completed at the time when the electronic money equivalent to the payment amount is withdrawn from the account of the user U.

[0029] Furthermore, the payment using the terminal device 10 may not only be a process of transferring electronic money from an account to which the user U has previously charged electronic money to an account of a specific store, but may also be, for example, a payment using a credit card registered in advance by the user U. In such a case, for example, the terminal device 10 may transfer electronic money in an amount indicated by the payment amount to the account of the specific store, and may also bill the operating company of the user U's credit card for the amount indicated by the payment amount.

[0030] In addition, the settlement using the terminal device 10 is not limited to the process of transferring electronic money from the account of user U to the account of a predetermined store. For example, it may be a settlement for transferring electronic money from the account of user U to the account of another user (i.e., money transfer between users). For example, the terminal device 10 used by the remitting user U reads the user identification information for identifying the recipient user (for example, the user identification information displayed on the terminal device 10 used by the recipient user), accepts the input of the transfer amount from user U, and transmits information indicating the read identification information, the transfer amount, and the user identification information for identifying user U to the settlement service providing device 20. In such a case, the settlement service providing device 20 transfers the amount of electronic money indicated by the transfer amount from the account of user U to the account of the recipient user, and notifies the completion of the transfer by outputting a screen or a predetermined sound indicating that the transfer has been completed to the terminal device 10 or the terminal device used by the recipient user.

[0031] Note that the money transfer using the terminal device 10 is not limited to the above-described process. For example, the money transfer using the terminal device 10 may be performed by inputting the recipient user's phone number or information indicating the recipient user (for example, user ID) into the terminal device 10. To give a specific example, the terminal device 10 accepts the input of the recipient user's phone number or user ID and the transfer amount from user U, and transmits the input phone number or user ID, the transfer amount, and the user identification information for identifying user U to the settlement service providing device 20. Then, the settlement service providing device 20 transfers the amount of electronic money indicated by the transfer amount from the account of user U to the account of the user associated with the transmitted phone number or user ID.

[0032] Here, the telephone number or user ID of the remittance destination user may be linked to information about the user and registered in advance in the payment app. In this case, terminal device 10 accepts from user U the designation of a user (remittance destination) registered in the payment app and an input of the remittance amount to the user, and transmits to payment service providing device 20 the telephone number or user ID linked to the designated user, the remittance amount, and user identification information that identifies user U.

[0033] Furthermore, for example, remittance using terminal device 10 may be performed by providing link information for receiving the remittance amount to the remittance user. As a specific example, terminal device 10 accepts input of the remittance amount from user U, generates link information for receiving the remittance amount, and provides the link information to the terminal device used by the remittance user by sending an email including the link information or posting information including the link information on a social networking service (SNS). Then, when the remittance user selects the link information and performs a receiving operation, payment service providing device 20 transfers electronic money in an amount indicated by the remittance amount from the account of user U to the account of the remittance user.

[0034] The above-mentioned payment means and payment services are not limited to those for providing a price (settlement of debt) for purchasing a product or providing a service. For example, as described above, the payment means and payment services may have a function related to remittance between accounts held by multiple users. That is, the above-mentioned payment means and payment services may be services that control the transmission and reception of electronic money between accounts of any owner linked to the owner of electronic money, such as a user or a store. That is, the payment means and payment services according to the embodiment may be provided in any form as long as they are transaction means and transaction services that execute various controls for realizing the exchange of electronic money (not only various inter-account remittance controls via electronic money, but also controls related to exchanges between electronic money accounts and bank accounts, various claim processes such as installments and processes associated with bonus payments, and various controls related to the exchange of assets including electronic money). In addition, the various controls realized by such transaction means and transaction services may include both control related to payment and control related to remittance, or only one of them. That is, a "transaction" is a concept that includes not only "settlement" related to electronic money, but also "remittance" of electronic money and various other processes. In other words, payment service providing apparatus 20 may be an information processing apparatus that realizes a transaction means for controlling the exchange of electronic money between any owners.

[0035] (1-3. Overview of Information Processing According to the Embodiment) An overview of the information processing according to the embodiment will be described below with reference to Fig. 2. Fig. 2 is a diagram for explaining the overview of the information processing according to the embodiment. The information processing according to the embodiment is executed by an information processing device 100.

[0036] As shown in Fig. 2, payment service providing device 20 executes various processes related to the electronic payment service provided to user U. Payment service providing device 20 acquires usage history information indicating the usage history of the electronic payment service by user U, through a payment app provided to user U. The usage history information includes information indicating the content of user U's actions performed using the payment app and information indicating the content of user U's operations performed on the payment app.

[0037] Payment service providing device 20 provides the usage history information to information processing device 100. Payment service providing device 20 may provide the usage history information by transmitting the usage history information in response to a request from information processing device 100, or may provide the usage history information to information processing device 100 by performing data linkage processing using a predetermined API (Application Programming Interface). Information processing device 100 internally stores and manages the usage history information provided by payment service providing device 20.

[0038] The operator device 30 transmits a processing request to the information processing device 100 in accordance with an operation of an operator OP (step S01).

[0039] When the information processing device 100 receives a processing request from the operator device 30, the information processing device 100 acquires usage history information (step S02).

[0040] In addition, the information processing device 100 estimates attribute information indicating attributes of the user U, who is a service user, based on the acquired usage history information (step S03), and provides the estimation result to the operator device 30 by transmitting it (step S04).

[0041] The estimation of attribute information will be specifically described. The information processing device 100 uses the usage history information of multiple users U (an example of "second users") as learning data, and uses attribute information indicating each of the multiple users U as teacher data to make a model learn the correspondence between the usage history information and the attribute information by machine learning. In addition, the information processing device 100 acquires the usage history information of a target user (an example of "first user") whose attributes are to be estimated, and estimates the attribute information corresponding to the target user based on the acquired usage history information and information indicating the correspondence obtained as a result of machine learning.

[0042] The information processing device 100 estimates likely attributes as attributes of the target user based on the content of the behavior of the user U performed using the payment app, the content of the operation of the user U performed on the payment app, etc. The information processing device 100 does not accurately estimate the attributes of the target user, but estimates likely attributes as attributes of the target user. The attributes of the target user estimated by the information processing device 100 are, for example, age, but are not particularly limited to age, and may be gender, family structure, annual income, etc.

[0043] For example, the information processing device 100 may use behavioral information indicating the contents of the behaviors of multiple users U performed in a payment application (an example of a "predetermined application") for using an electronic payment service as learning data, and may learn the correspondence between the behavioral information and the attribute information into a model. The information processing device 100 may then acquire the behavioral information of a target user as usage history information, and estimate the attribute information corresponding to the target user based on the acquired behavioral information and information indicating the correspondence.

[0044] The behavioral information may include at least one of a payment history regarding payments made through the payment app, a remittance history regarding remittances made through the payment app, a viewing history of notifications provided to user U through the payment app, a coupon acquisition history provided to user U through the payment app, a recharge history of money balance by user U through the payment app, and a usage history of a stamp card provided to user U through the payment app. In addition, the behavioral information may include a recharge amount, a recharge date and time, a recharge method, an auto-recharge setting status, and the like in relation to the recharge history of money balance. Examples of the recharge method include bank transfer and credit card.

[0045] The payment history may include, for each payment, a combination of information indicating the payment amount and information indicating the payment date and time. The payment history may include, for each payment, a combination of a store category that is set in advance to classify the store where the payment was made, information indicating the payment amount, and information indicating the payment date and time. The information processing device 100 can also acquire payment history for a specific timing selected by the operator OP. Examples of specific timing include long holidays, Christmas, and the New Year holidays. The remittance history may include a combination of information indicating the remittance amount and information indicating the remittance date and time for each remittance. The information processing device 100 can also acquire remittance history for a specific timing selected by the operator OP.

[0046] Furthermore, the information processing device 100 may use payment operation information indicating operations related to payments by multiple users U performed in a payment app as learning data, and may learn a correspondence relationship between the payment operation information and attribute information as a model. The information processing device 100 may acquire the payment operation information of the target user as usage history information, and estimate attribute information corresponding to the target user based on the acquired payment operation information and information indicating the correspondence relationship.

[0047] The payment operation information may include information indicating the operation content executed by the user U until the payment is executed using the payment application. The information indicating the operation content may include the types of icons and buttons operated by the user U in the payment application to reach the payment screen, and the types of payment methods finally used for payment (for example, barcode payment or scan payment). Alternatively, the information indicating the operation content may include information indicating screen transitions (page transitions). For example, when the user can select whether to make a payment using the code displayed small on the top page of the payment application or the code displayed large specifically for payment, the information indicating the screen transition (page transition) until the code used for payment is displayed may also be included in the information indicating the operation content.

[0048] As described above, according to the information processing according to the embodiment, the information processing apparatus 100 acquires the usage history information of the target user whose attributes are to be estimated, and based on the acquired usage history information and the information indicating the correspondence relationship obtained as a result of machine learning, estimates the attribute information corresponding to the target user. The information processing apparatus 100 estimates a likely age as the age of the target user, for example, based on histories such as payments and money transfers using an electronic payment service, and operation histories indicating operation contents on the payment application. From this, the information processing apparatus 100 can assist in estimating likely attributes for the target user.

[0049] [2. Configuration of Information Processing Apparatus 100] Hereinafter, an example of the functional configuration of the information processing apparatus 100 according to the embodiment will be described with reference to FIG. 3. FIG. 3 is a diagram showing a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 3, the information processing apparatus 100 according to the embodiment includes a communication unit 110, a storage unit 120, and a control unit 130.

[0050] (Communication Unit 110) The communication unit 110 is realized by, for example, a communication module, a NIC (Network Interface Card), or the like. The communication unit 110 is connected to the network N, either wired or wirelessly, and transmits and receives information to and from other devices such as the payment service providing device 20 and the operator device 30.

[0051] (Memory unit 120) The memory unit 120 stores programs and data used for control and calculation by the control unit 130, for example. The memory unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 3, the memory unit 120 has a usage history information DB (Data Base) 121 and a correspondence relationship information DB 122.

[0052] (Usage history information DB121) The usage history information DB121 stores usage history information indicating the usage history of the electronic payment service by the user U. The information processing device 100 acquires the usage history information from the payment service providing device 20. FIG. 4 is a diagram showing an overview of the usage history information according to the embodiment.

[0053] As shown in FIG. 4, the usage history information stored in the usage history information DB121 has an item of "user ID" and an item of "usage history information". These items included in the usage history information are associated with each other.

[0054] The item of "user ID" stores the user ID, which is unique identification information of the user U who is the service user of the electronic payment service.

[0055] The "usage history information" field stores usage history information of an electronic payment service provided via a terminal device used by a service user of the electronic payment service. The "usage history information" field may store, as usage history information, behavioral information indicating the content of actions taken in a payment app for using the electronic payment service for a user U who is a service user of the electronic payment service.

[0056] The behavioral information may include at least one of a payment history regarding payments made through the payment app, a remittance history regarding remittances made through the payment app, a viewing history of notifications provided to user U through the payment app, a coupon acquisition history provided to user U through the payment app, a recharge history of money balance by user U through the payment app, and a usage history of a stamp card provided to user U through the payment app. In addition, the behavioral information may include a recharge amount, a recharge date and time, a recharge method, an auto-recharge setting status, etc., related to the recharge history of money balance. Examples of the recharge method include bank transfer and credit card.

[0057] The payment history may include, for each payment, a combination of information indicating the payment amount and information indicating the payment date and time. The payment history may also include, for each payment, a combination of a store category that is preset to classify the store where the payment was made, information indicating the payment amount, and information indicating the payment date and time. The payment history may also acquire a payment history for a specific timing selected by the operator OP. Examples of specific timing include long holidays, Christmas, and the New Year holidays. The remittance history may include a combination of information indicating the remittance amount and information indicating the remittance date and time for each remittance. The information processing device 100 may also acquire a remittance payment history for a specific timing selected by the operator OP.

[0058] Furthermore, the usage history information stored in the usage history information DB 121 may include payment operation information indicating operations related to payments made by a plurality of users U in the payment application.

[0059] The payment operation information may include information indicating the operation contents performed by the user U before the payment is executed using the payment app. The information indicating the operation contents may include the type of icon or button operated by the user U in the payment app to reach the payment screen, the type of payment method finally used for the payment (for example, barcode payment or scan payment), etc.

[0060] (Correspondence information DB122) The correspondence information DB122 uses usage history information of multiple users U as learning data and attribute information indicating the attributes of each of the multiple users U as teaching data, and stores information indicating the correspondence obtained as a result of machine learning by having a model learn the correspondence between the usage history information and the attribute information through machine learning.

[0061] (Control unit 130) The control unit 130 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs (an example of an "information processing program" according to an embodiment) stored in a storage device inside the information processing device 100 using the RAM as a working area.

[0062] Furthermore, the control unit 130 may be realized by an integrated circuit such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a general purpose graphic processing unit (GPGPU).

[0063] 3, the control unit 130 has an acquisition unit 131, an estimation unit 132, and a learning unit 133, and these units realize or execute the functions and actions of information processing described below. Note that the control unit 130 may have new functional units different from the units shown in FIG. 3 in response to the extension of various processes executed by the information processing device 100.

[0064] (Acquisition part 131) When the acquisition unit 131 receives a processing request from the operator OP through the communication unit 110, the acquisition unit 131 acquires usage history information of a target user whose attributes are to be estimated from the usage history information DB 121. For example, the acquisition unit 131 randomly selects a target user from among a plurality of users U.

[0065] (Estimation part 132) The estimation unit 132 estimates attribute information indicating attributes of a service user based on the usage history information acquired by the acquisition unit 131. For example, the estimation unit 132 estimates attribute information corresponding to a target user based on the usage history information of the target user acquired by the acquisition unit 131 and information indicating a correspondence obtained as a result of machine learning by the learning unit 133. The estimation unit 132 transmits the estimation result to the operator device 30 via the communication unit 110, thereby providing the estimation result to the operator OP.

[0066] (Learning Section 133) The learning unit 133 uses the usage history information of multiple users U who are service users as learning data, and uses attribute information indicating the attributes of each of the multiple users U as teacher data to learn a correspondence relationship between the usage history information and the attribute information into a model by machine learning. The learning data used by the learning unit 133 for learning may be normalized using logarithms or the like.

[0067] The models used by the learning unit 133 for learning include, for example, decision trees, regression models, neural networks, etc., but are not limited to such examples. Examples of decision trees include GBDT (Gradient Boosting Decision Tree) such as XGBoost (eXtreme Gradient Boosting), LightGBM (Light Gradient Boosting Machine), and CatBoost (Category Boosting), but are not limited to such examples.

[0068] The estimation method of the attributes of the target user realized by each part of the control unit 130 and the combination of each part will be described. For example, the learning unit 133 uses, as learning data, the behavior information indicating the content of the behaviors of a plurality of users U performed in a payment application for using an electronic payment service, and causes the model to learn the correspondence relationship between the behavior information and the attribute information. The learning unit 133 stores the information indicating the correspondence relationship obtained as a result of machine learning in the correspondence relationship information DB122. The acquisition unit 131 acquires the behavior information of the target user as usage history information. The estimation unit 132 estimates the attribute information corresponding to the target user based on the behavior information of the target user acquired by the acquisition unit 131 and the information indicating the correspondence relationship obtained as a result of machine learning by the learning unit 133.

[0069] Also, for example, the learning unit 133 uses, as learning data, the payment operation information indicating the payment-related operations of a plurality of users U performed in a payment application for using an electronic payment service, and causes the model to learn the correspondence relationship between the behavior information and the attribute information. The learning unit 133 stores the information indicating the correspondence relationship obtained as a result of machine learning in the correspondence relationship information DB122. The acquisition unit 131 acquires the payment operation information of the target user as usage history information. The estimation unit 132 estimates the attribute information corresponding to the target user based on the behavior information of the target user acquired by the acquisition unit 131 and the information indicating the correspondence relationship obtained as a result of machine learning by the learning unit 133.

[0070] 〔3. Example of processing procedure〕 Hereinafter, a flow of information processing executed by the information processing device 100 according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a flowchart showing an example of a processing procedure of information processing executed by the information processing device 100 according to the embodiment. The processing procedure shown in Fig. 5 is executed by the control unit 130 included in the information processing device 100. The control unit 130 repeatedly executes the processing procedure shown in Fig. 5 while the information processing device 100 is operating.

[0071] As shown in FIG. 5, the acquisition unit 131 acquires the usage history information of a target user whose attributes are to be estimated from the usage history information DB 121 (Step S101).

[0072] The estimation unit 132 estimates attribute information corresponding to the target user based on the usage history information of the target user acquired by the acquisition unit 131 and information indicating the correspondence obtained as a result of machine learning by the learning unit 133 (step S102).

[0073] Furthermore, the estimation unit 132 transmits the estimation result to the operator device 30 via the communication unit 110, thereby providing it to the operator OP (step S103), and ends the processing procedure shown in FIG.

[0074] 4. Modifications (4-1. About usage history information) In the above-described embodiment, the information processing device 100 may store, as the usage history information, information about following stores in the payment app. Examples of the information about following stores include the number of followed stores that are registered as favorites in the payment app, the number of followed stores by store category, and the like.

[0075] (4-2. System configuration, etc.) In the above embodiment, an example has been described in which information processing device 100 according to the embodiment executes the information processing according to the embodiment, but the present invention is not limited to this example. For example, payment service providing device 20 may execute the information processing according to the embodiment. In this case, it is sufficient that payment service providing device 20 has the functions that information processing device 100 has for executing the information processing according to the embodiment.

[0076] In addition, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, and conversely, all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0077] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0078] Furthermore, the above-described embodiments can be appropriately combined as long as the processing contents are not contradictory.

[0079] [5. Hardware Configuration] Moreover, the information processing device 100 according to the above-described embodiment or modification is realized, for example, by a computer 1000 having a configuration as shown in Fig. 6. Fig. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 100 according to the embodiment or modification.

[0080] The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which an arithmetic unit 1030, a primary storage device 1040, a secondary storage device 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected via a bus 1090.

[0081] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050 and programs read from the input device 1020, and executes various processes. The primary storage device 1040 is a memory device, such as a RAM, that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used by the arithmetic device 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), HDD, flash memory, etc.

[0082] The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or a printer, and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface), a registered trademark. The input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, and scanner, and is realized by a USB, for example.

[0083] The input device 1020 may be a device that reads information from an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. The input device 1020 may also be an external storage medium such as a USB memory.

[0084] The network IF 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0085] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0086] For example, when the computer 1000 functions as the information processing device 100 according to the embodiment or the modification, the arithmetic device 1030 of the computer 1000 executes a program loaded onto the primary storage device 1040 to realize functions similar to those of the control unit 130. That is, the arithmetic device 1030 realizes processing by the information processing device 100 according to the embodiment or the modification in cooperation with a program (for example, an example of an information processing program) loaded onto the primary storage device 1040.

[0087] 6. Effects As described above, the information processing device 100 according to the embodiment includes the acquisition unit 131 and the estimation unit 132. The acquisition unit 131 acquires usage history information of an electronic payment service provided via a terminal device used by a service user of the electronic payment service. The estimation unit 132 estimates attribute information indicating attributes of the service user based on the usage history information acquired by the acquisition unit.

[0088] Moreover, the information processing device 100 according to the embodiment includes a learning unit 133. The learning unit 133 uses the usage history information of a plurality of users U (an example of a "second user") who are service users as learning data, and uses attribute information indicating each of the plurality of users U as teacher data, and causes a model to learn a correspondence relationship between the usage history information and the attribute information by machine learning. The acquisition unit 131 acquires the usage history information of a target user (an example of a "first user") whose attributes are to be estimated. The estimation unit 132 may estimate attribute information corresponding to the target user based on the usage history information of the target user acquired by the acquisition unit 131 and information indicating the correspondence relationship obtained as a result of the machine learning by the learning unit 133.

[0089] The learning unit 133 may use behavioral information indicating the contents of the behaviors of multiple users U performed in a payment app (an example of a "predetermined application") for using an electronic payment service as learning data, and may cause a model to learn the correspondence between the behavioral information and the attribute information. In this case, the acquisition unit 131 may acquire behavioral information of the target user as the usage history information. Then, the estimation unit 132 may estimate attribute information corresponding to the target user based on the behavioral information of the target user acquired by the acquisition unit 131 and information indicating the correspondence obtained as a result of machine learning by the learning unit 133.

[0090] In addition, the behavioral information may include at least one of a payment history regarding payments made through the payment app, a remittance history regarding remittances made through the payment app, a viewing history of notifications provided to user U through the payment app, a coupon acquisition history provided to user U through the payment app, a money balance recharge history made by user U through the payment app, and a usage history of a stamp card provided to user U through the payment app.

[0091] Furthermore, the payment history may include, for each payment, a combination of information indicating the payment amount and information indicating the payment date and time.

[0092] In addition, the payment history may include, for each payment, a combination of a store category that is set in advance to classify the store where the payment was made, information indicating the payment amount, and information indicating the date and time of the payment.

[0093] The remittance history may also include, for each remittance, a combination of information indicating the remittance amount and information indicating the remittance date and time.

[0094] The learning unit 133 may use payment operation information indicating operations related to payments by multiple users U performed in a payment app for using an electronic payment service as learning data, and may learn a correspondence between the payment operation information and the attribute information as a model. In this case, the acquisition unit 131 may acquire the payment operation information of the target user as the usage history information. Then, the estimation unit 132 may estimate the attribute information corresponding to the target user based on the payment operation information of the target user acquired by the acquisition unit 131 and information indicating the correspondence obtained as a result of machine learning by the learning unit 133.

[0095] Furthermore, the payment operation information may include information indicating the contents of operations performed by the user U before the payment is made using the payment app.

[0096] In this way, the information processing device 100 according to the embodiment acquires usage history information of a target user whose attributes are to be estimated, and estimates attribute information corresponding to the target user based on the acquired usage history information and information indicating a correspondence relationship obtained as a result of machine learning. The information processing device 100 estimates a likely age as the target user's age based on, for example, a history of payments and remittances using an electronic payment service, an operation history indicating the operation content on a payment app, and the like. In this way, the information processing device 100 can support the estimation of likely attributes for a user.

[0097] The above-mentioned effects can be realized by the processing executed by each of the above-mentioned units, or any combination of the processing executed by each unit.

[0098] [7. Other] Although some of the embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section.

[0099] Further, the information processing device 100 described above can flexibly change its configuration, for example, by calling an external platform or the like using an API (Application Programming Interface) or network computing to realize some functions.

[0100] Furthermore, the term "unit" in the claims may be read as "means" or "circuit," etc. For example, a control unit may be read as control means or a control circuit. [Explanation of symbols]

[0101] SYS Information Processing System 10 Terminal Equipment 100 Information processing device 110 Communications Department 120 Storage section 121 Usage History Information DB 122 Correspondence information DB 130 Control section 131 Acquisition Department 132 Estimation Department 133 Learning Department

Claims

1. an acquisition unit that acquires, as information provided via a terminal device used by a service user of an electronic payment service, behavioral information indicating the content of behaviors performed by a plurality of second users who are the service users, a payment history relating to payments made at specific times through a predetermined application for using the electronic payment service and a remittance history relating to remittances made at specific times through the predetermined application; an estimation unit that estimates attribute information indicating attributes of the service user based on the payment history and the remittance history acquired by the acquisition unit; a learning unit that uses the payment histories and the remittance histories of the plurality of second users as learning data and attribute information indicating attributes of each of the plurality of second users as training data, and learns a correspondence relationship between the payment histories and the remittance histories and the attribute information into a model by machine learning; having The acquisition unit is Acquire the payment history and the remittance history of the first user whose attribute information is to be estimated; The estimation unit is The attribute information corresponding to the first user is estimated based on the payment history and the remittance history of the first user acquired by the acquisition unit and information indicating the correspondence relationship.

23. An information processing apparatus comprising:

2. an acquisition unit that acquires, as information provided via a terminal device used by a service user of an electronic payment service, behavioral information indicating the content of behaviors performed by a plurality of second users who are the service users, including a browsing history of notifications provided to the service user through a predetermined application for using the electronic payment service, an acquisition history of coupons provided to the service user through the predetermined application, and a usage history of a stamp card provided to the service user through the predetermined application; an estimation unit that estimates attribute information indicating attributes of the service user based on the browsing history, the acquisition history, and the usage history acquired by the acquisition unit; a learning unit that uses the browsing history, the acquisition history, and the usage history of the plurality of second users as learning data and attribute information indicating attributes of each of the plurality of second users as teacher data, and learns a correspondence relationship between the browsing history, the acquisition history, and the usage history and the attribute information into a model by machine learning; having The acquisition unit is Acquire the browsing history, the acquisition history, and the usage history of a first user who is a target of estimating the attribute information; The estimation unit is The attribute information corresponding to the first user is estimated based on the browsing history, the acquisition history, and the information indicating the correspondence between the usage history and the first user acquired by the acquisition unit.

23. An information processing apparatus comprising:

3. The payment history is For each payment, a combination of information indicating a payment amount and information indicating a payment date and time is included.

2. The information processing apparatus according to claim 1,

4. The settlement history is For each payment, a combination of a store category that is set in advance to classify the store where the payment is made, information indicating the payment amount, and information indicating the date and time of the payment is included.

2. The information processing apparatus according to claim 1,

5. The remittance history is For each remittance, a combination of information indicating the remittance amount and information indicating the remittance date and time is included.

2. The information processing apparatus according to claim 1,

6. an acquisition unit that acquires behavioral information provided via a terminal device used by a service user of an electronic payment service, the behavioral information indicating the content of behaviors performed by a plurality of second users who are the service users in a predetermined application for using the electronic payment service; an estimation unit that estimates attribute information indicating attributes of the service user based on the behavior information acquired by the acquisition unit; a learning unit that uses payment operation information indicating operations related to payments by the plurality of second users as learning data and age information indicating the ages of each of the plurality of second users as teacher data, and that learns a correspondence relationship between the payment operation information and the age information into a model by machine learning; having The acquisition unit is As the behavioral information, the payment operation information of a first user who is a service user is acquired; The estimation unit is The age information corresponding to the first user is estimated based on the payment operation information of the first user acquired by the acquisition unit and the information indicating the correspondence relationship.

23. An information processing apparatus comprising:

7. The payment operation information is The information includes information indicating the operation contents performed by the service user before the settlement is executed using the predetermined application.

7. The information processing apparatus according to claim 6,

8. 1. A computer-implemented information processing method, comprising: an acquisition step of acquiring information provided via a terminal device used by a service user of an electronic payment service, the information being behavioral information indicating the content of behaviors performed by a plurality of second users who are said service users, including a payment history relating to payments made at specific times through a predetermined application for using said electronic payment service and a remittance history relating to remittances made at specific times through said predetermined application; an estimation step of estimating attribute information indicating attributes of the service user based on the settlement history and the remittance history acquired in the acquisition step; a learning process in which the payment histories and the remittance histories of the second users are used as learning data, and attribute information indicating attributes of each of the second users is used as training data, and a model is trained by machine learning to learn a correspondence between the payment histories and the remittance histories and the attribute information; Including, The obtaining step includes: Acquire the payment history and the remittance history of the first user whose attribute information is to be estimated; The estimation step includes: The attribute information corresponding to the first user is estimated based on the payment history and the remittance history of the first user acquired in the acquiring step and information indicating the correspondence relationship.

23. An information processing method comprising:

9. On the computer, an acquisition step of acquiring information provided via a terminal device used by a service user of an electronic payment service, the information being behavioral information indicating the content of behaviors performed by a plurality of second users who are said service users, including a payment history relating to payments made at specific times through a predetermined application for using said electronic payment service and a remittance history relating to remittances made at specific times through said predetermined application; an estimation step of estimating attribute information indicating attributes of the service user based on the payment history and the remittance history acquired by the acquisition step; a learning step of learning a correspondence relationship between the payment history and the remittance history of the second users and the attribute information indicating each of the second users as training data by machine learning; Run the command, The acquisition step includes: Acquire the payment history and the remittance history of the first user whose attribute information is to be estimated; The estimation procedure comprises: The attribute information corresponding to the first user is estimated based on the payment history and the remittance history of the first user acquired by the acquisition step and information indicating the correspondence relationship.

2. An information processing program comprising:

10. 1. A computer-implemented information processing method, comprising: an acquisition step of acquiring information provided via a terminal device used by a service user of an electronic payment service, the information being behavioral information indicating the content of behaviors performed by a plurality of second users who are the service users, including a browsing history of notifications provided to the service user through a predetermined application for using the electronic payment service, an acquisition history of coupons provided to the service user through the predetermined application, and a usage history of a stamp card provided to the service user through the predetermined application; an estimation step of estimating attribute information indicating attributes of the service user based on the browsing history, the acquisition history, and the usage history acquired by the acquisition step; a learning process in which the browsing history, the acquisition history, and the usage history of the plurality of second users are used as learning data, and attribute information indicating attributes of each of the plurality of second users is used as training data, and a correspondence relationship between the browsing history, the acquisition history, and the usage history and the attribute information is learned into a model by machine learning; Including, The obtaining step includes: Acquire the browsing history, the acquisition history, and the usage history of a first user who is a target of estimating the attribute information; The estimation step includes: The attribute information corresponding to the first user is estimated based on the browsing history, the acquisition history, and the information indicating the correspondence between the usage history and the first user acquired in the acquiring step.

23. An information processing method comprising:

11. On the computer, an acquisition step of acquiring information provided via a terminal device used by a service user of an electronic payment service, the information being behavioral information indicating the content of behaviors performed by a plurality of second users who are the service users, including a browsing history of notifications provided to the service user through a specified application for using the electronic payment service, an acquisition history of coupons provided to the service user through the specified application, and a usage history of a stamp card provided to the service user through the specified application; an estimation step of estimating attribute information indicating attributes of the service user based on the browsing history, the acquisition history, and the usage history acquired by the acquisition step; a learning step of learning a correspondence relationship between the browsing history, the acquisition history, and the usage history of the plurality of second users and the attribute information by machine learning using the browsing history, the acquisition history, and the usage history of the plurality of second users as learning data and attribute information indicating attributes of each of the plurality of second users as training data; Run the command, The acquisition step includes: Acquire the browsing history, the acquisition history, and the usage history of a first user who is a target of estimating the attribute information; The estimation procedure comprises: The attribute information corresponding to the first user is estimated based on the browsing history, the acquisition history, and the information indicating the correspondence between the usage history and the first user acquired by the acquisition step.

2. An information processing program comprising:

12. 1. A computer-implemented information processing method, comprising: an acquisition step of acquiring behavioral information provided via a terminal device used by a service user of an electronic payment service, the behavioral information indicating the content of behaviors performed by a plurality of second users who are the service users in a predetermined application for using the electronic payment service; an estimation step of estimating attribute information indicating attributes of the service user based on the behavior information acquired by the acquisition step; a learning process in which payment operation information indicating operations related to payments by the plurality of second users is used as learning data, and age information indicating the ages of each of the plurality of second users is used as training data, and a correspondence relationship between the payment operation information and the age information is learned into a model by machine learning; Including, The obtaining step includes: As the behavioral information, the payment operation information of a first user who is a service user is acquired; The estimation step includes: The age information corresponding to the first user is estimated based on the payment operation information of the first user acquired in the acquiring step and the information indicating the correspondence relationship.

23. An information processing method comprising:

13. On the computer, an acquisition step of acquiring behavioral information provided via a terminal device used by a service user of an electronic payment service, the behavioral information indicating the content of behaviors performed by a plurality of second users who are the service users in a predetermined application for using the electronic payment service; an estimation step of estimating attribute information indicating attributes of the service user based on the behavior information acquired by the acquisition step; a learning step of learning a correspondence relationship between the payment operation information and the age information into a model by machine learning using payment operation information indicating operations related to payments by the plurality of second users as learning data and age information indicating the ages of each of the plurality of second users as training data; Run the command, The acquisition step includes: As the behavioral information, the payment operation information of a first user who is a service user is acquired; The estimation procedure comprises: The age information corresponding to the first user is estimated based on the payment operation information of the first user acquired by the acquisition step and the information indicating the correspondence relationship.

2. An information processing program comprising:

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