Information processing device and information processing method

Abstract

An information processing device according to one embodiment comprises: a first acquisition unit that acquires a first score indicating the degree to which a user is IT literate, the first score being calculated on the basis of a first history indicating a history of the user utilizing a service; a second acquisition unit that acquires a second score indicating a reception type preferred by the user, the second score being calculated on the basis of an estimation of the user's personality; and an output unit that outputs information corresponding to the first score and to the second score. The information processing device has a calculation unit that calculates the second score using AI and service-related information related to a service utilized by the user using a portable terminal. The second acquisition unit acquires the second score from the calculation unit.

Description

Information processing device and information processing method

[0001] The present invention relates to a technique for an information processing device and an information processing method.

[0002] There are known technologies for supporting sales activities. For example, Patent Document 1 discloses an invention for estimating the level of IT literacy of a customer in relation to sales activities related to IT services.

[0003] Patent No. 5965531

[0004] The invention described in Patent Document 1 merely utilizes the degree of IT literacy of customers in sales activities.

[0005] In contrast, the present invention provides improved information to assist in improving the quality of user interaction.

[0006] An information processing device according to one aspect of the present disclosure includes a first acquisition unit that acquires a first score indicating the level of IT literacy of a user, calculated based on a first history indicating the user's history of using a service; a second acquisition unit that acquires a second score that indicates the user's preferred type of response, calculated based on an estimation of the user's personality; and an output unit that outputs information corresponding to the first score and the second score.

[0007] An information processing method according to another aspect of the present disclosure includes the steps of: acquiring a first score indicating the level of IT literacy of a user, the first score being calculated based on a first history indicating the user's history of using a service; acquiring a second score indicating the user's preferred type of response, the second score being calculated based on an estimation of the user's personality; and outputting information corresponding to the first score and the second score.

[0008] According to the present invention, improved information can be provided to support improvement of the quality of customer service.

[0009] 1 is a diagram illustrating an example of a system configuration of an information processing system 1 according to an embodiment. A diagram illustrating an example of a functional configuration of the information processing system 1. A diagram illustrating an example of a hardware configuration of an information processing device 10. A sequence chart illustrating an example of an operation overview in the information processing system 1. A diagram illustrating an example of a user database 1000. A diagram illustrating an example of first information 1001. A diagram illustrating an example of second information 2001. A flowchart illustrating an example of a method for calculating a first score in the information processing system 1. A diagram illustrating an example of a first score database 1002. A diagram illustrating an example of a first information list 1003. A flowchart illustrating an example of a method for calculating a second score in the information processing system 1. A diagram illustrating an example of an item database 2002. A diagram illustrating an example of a reference value list 2003. A diagram illustrating an example of a factor score 2004. A diagram illustrating an example of a second information list 2005.

[0010] 1. Configuration FIG. 1 illustrates an exemplary system configuration of an information processing system 1 according to an embodiment. In this example, the information processing system 1 (or simply the system) is a system for supporting telecommunications carriers (officially referred to as "telecommunications carriers") in improving the quality of customer service provided to users. A telecommunications carrier (also referred to as a "telecommunications carrier") is a company, corporation, or business entity that provides communication services via wireless communication terminals (or simply mobile terminals or terminals), such as smartphones. A user is a user who uses a wireless communication line of a telecommunications carrier (who has signed a mobile communication contract) and is considered a customer from the perspective of the telecommunications carrier. A user is an end user. Customer service is a general term for customer service (or customer service work) in which a telecommunications carrier employee and a user communicate directly (or indirectly) through various communication modes, such as face-to-face, telephone, email, or chat. In the following description, a person who serves a user is referred to as a "service provider." A service provider is a human being, and is an employee of the telecommunications carrier or a person commissioned by the telecommunications carrier.

[0011] In recent years, with the advancement of smartphone technology and its growing necessity in daily life, the services offered by telecommunications carriers have become increasingly diverse and multifunctional. In this example, services include, for example, a communication line contract (usage), a device purchase, warranty services, and various web services. When users use these services, they often receive support from a representative to complete various procedures related to the contract, usage, and warranty. Expanding support from telecommunications carriers is a challenge. Therefore, telecommunications carrier employees involved in these services are increasingly required to provide appropriate responses (dealings) tailored to users' needs. In particular, based on the business characteristics of advanced technologies such as smartphones and the characteristics of work that involves direct interaction with end users (an example of a user), the inventors focused on two perspectives to ensure appropriate user support: (A) level of IT literacy and (B) the user's preferred type of support.

[0012] First, the level of IT literacy is a perspective that expresses the degree of knowledge of IT technology, understanding of services, or proficiency in using (operating) terminals that the user being served possesses. The level of IT literacy correlates with the degree of web channel utilization. The degree of web channel utilization is an index showing the extent to which a user uses means (channels or routes) using the Internet (online) to receive services. It is thought that there is little need for a service representative to provide excessive technical support or spend time on users who are capable of fully utilizing web channels (it is sufficient to guide them to procedures using web channels). Conversely, it is likely that it is preferable to provide sufficient support intervention to users whose IT literacy is not so high.

[0013] Next, the user's preferred response type is a viewpoint that represents an index (categorized index) that indicates the depth of communication that the user desires from the user when communicating with the user. In the present invention, the user's preferred response types are distinguished (classified) as one being "polite" and the other being "succinct." In other words, if the user prefers a more polite response, the user needs to strive to provide a response based on more thorough communication. On the other hand, if the user prefers a more succinct response over politeness, the user should avoid excessive communication and provide a response that is limited to the bare essentials.

[0014] Based on this perspective, there are various benefits for both users and attendants. From the user's perspective, they can receive appropriate customer service, which satisfies their needs for completing procedures, resolving problems, and providing high quality service. Attendees can also expect benefits such as more efficient customer service, faster and more accurate customer service, and higher customer satisfaction. Therefore, the present invention achieves the above objectives based on the following system.

[0015] The information processing system 1 includes an information processing device 10, a user terminal 20, a customer service terminal 30, and an information collection server 40. In this example, the components of the system are connected via a network 9 as shown in Fig. 1. In this example, the network 9 is a computer network such as the Internet or a mobile network. Note that Fig. 1 schematically illustrates a customer service representative serving a user (so-called in-store customer service) at a physical store (or simply called a store) owned by a telecommunications carrier.

[0016] The information processing device 10 is an information processing device or server device in the information processing system 1. In this example, the information processing device 10 is connected to a user terminal 20 via a network 9 and acquires (performs data communication with) various information and history of a target user (hereinafter referred to as the "target user"). The history here refers to, for example, the target user's behavioral history (log) performed via the user terminal 20. The information processing device 10 outputs information (hereinafter referred to as "output information") based on two perspectives: the level of IT literacy and the user's preferred type of service to the service terminal 30. The output information is information intended to support the target user in improving the quality of user service.

[0017] The user terminal 20 (an example of a mobile terminal) is a terminal owned and used by a user U. The user terminal 20 includes, for example, a smartphone, a tablet, or a personal computer. The user U can use services via the user terminal 20. In this example, the user terminal 20 is connected to an information collection server 40 via a network and transmits various data related to the user U to the information collection server 40. The information collection server 40 owned by a telecommunications carrier can collect the behavioral history of each user, such as location information of the user terminal 20 or payment information via the user terminal 20. The telecommunications carrier can aggregate the behavioral history of multiple users using the information collection server 40. The data obtained by aggregation is referred to as aggregated data. The telecommunications carrier provides at least a portion of the behavioral history and aggregated data to the information processing device 10. Alternatively, each user terminal 20 may directly provide the behavioral history of its user to the information processing device 10.

[0018] The answering terminal 30 is a terminal operated by a person who is waiting. The answering terminal 30 includes, for example, a smartphone, a tablet, or a personal computer. The answering terminal 30 acquires output information of the target user from the information processing device 10. The person who is waiting acquires output information related to the waiting of the target user who is scheduled to be served via the answering terminal 30. The answering terminal 30 can present the output information in various formats. For example, the answering terminal 30 is connected to an external monitor, an external printer, or other peripheral devices. The answering terminal 30 outputs the output information to various devices in accordance with the operation of the person who is waiting. For example, the person who is waiting serves the user U while referring to the output information provided from the information processing device 10 at the store via the answering terminal 30 or the like.

[0019] 2 is a diagram illustrating an example of the functional configuration of the information processing system 1. In this embodiment, the information processing device 10 has functional blocks (components) including a first acquisition unit 11, a second acquisition unit 12, an output unit 13, a first calculation unit 14, a second calculation unit 15, a personality estimation unit 16, an information generation unit 17, a storage unit 191, and a control unit 192. In this example, the storage unit 191 stores various data and programs including a database, for example. In this example, the control unit 192 performs various controls.

[0020] The first acquisition unit 11 acquires a first score indicating the level of IT literacy of the user, calculated based on a first history indicating a history of the user's use of a service. In this example, the first score is a score indicating an index of the level of IT literacy. In this example, the first history includes, for example, a behavioral history of the user. The behavioral history is a history of actions related to services taken by the user via the user terminal 20. The information processing device 10 acquires the first history from the user terminal 20 via the information collection server 40. The first acquisition unit 11 transmits the first history acquired from the user terminal 20 to the first calculation unit 14. The first calculation unit 14 calculates the first score based on the first history. The first acquisition unit 11 acquires the first score from the first calculation unit 14.

[0021] The second acquisition unit 12 acquires a second score indicating the user's preferred type of service, calculated based on the user's personality estimation. In this example, the second score is a score indicating an index of the user's preferred type of service. The second acquisition unit 12 performs personality estimation of the user via the personality estimation unit 16. Personality estimation here refers to estimating the target user's own personality based on information acquired from the target user. Personality estimation here can be performed using a wide variety of methods, and may include, for example, personality estimation based on the user's internal or psychological scale (five dimensions) based on the so-called Big Five. The second acquisition unit 12 presents the result of the user's personality estimation to the second calculation unit 15. The second calculation unit 15 calculates the second score based on the user's personality estimation. The second acquisition unit 12 acquires the second score from the second calculation unit 15.

[0022] The output unit 13 outputs information (an example of "output information") according to the first score and the second score. The output unit 13 presents the first score and the second score to the information generation unit 17. The information generation unit 17 generates the output information based on the first score and the second score. The output unit 13 acquires the output information from the information generation unit 17. The output unit 13 outputs the output information to, for example, the answering terminal 30.

[0023] The first calculation unit 14 calculates a first score based on the first history. The first calculation unit 14 acquires the first history from the first acquisition unit 11. The first calculation unit 14 estimates the level of the user's (A) IT literacy based on the first history (behavioral history). The first calculation unit 14 calculates the first score and transmits it to the first acquisition unit 11.

[0024] The second calculation unit 15 (an example of a calculation unit) calculates the second score using service-related information and AI regarding services used by the user using the mobile terminal. The service-related information refers to various data related to services provided to the user using the user terminal 20. In this example, the service-related information may include any information related to the service provided using the user terminal 20, such as advance preparations for receiving the service (e.g., a contract) or information about the user terminal 20 while receiving the service (e.g., location information). In this example, the service-related information includes contract information and behavioral history. The contract information is, for example, information about the contract between the user and a communication carrier regarding the user terminal 20. The service-related information includes behavioral history (an example of a first history). In one embodiment, the service-related information includes a usage history of applications installed on the user's mobile terminal. The service-related information includes a usage history of the user's mobile terminal. The service-related information includes a history of location information of the mobile terminal. The service-related information includes subscriber information for mobile communications using the mobile terminal. In this example, the information processing device 10 can arbitrarily acquire the service-related information and the first history from the user terminal 20. The first history may be a concept that includes contract information.

[0025] The personality estimation unit 16 estimates the personality of the user. The personality estimation is performed using AI. The AI ​​includes a trained model trained using training data in which service-related information about multiple users is used as an explanatory variable and scores obtained from personality assessment questionnaire results administered to the multiple users are used as a target variable.

[0026] The information generation unit 17 generates output information according to the first score and the second score. The information generation unit 17 acquires the first score and the second score from the output unit 13. The information generation unit 17 identifies first information and second information corresponding to the first score and the second score, respectively. The output information (first information and second information) includes, for example, standard phrases, hints, cues, advice, or various information to support the response. The output information is set in advance according to the numerical values ​​of each score. The information generation unit 17 reads out the output information and inputs it into a predetermined format. The information generation unit 17 transmits data of the generated output information to the output unit 13.

[0027] FIG. 3 is a diagram illustrating an example of the hardware configuration of the information processing device 10. The information processing device 10 is physically configured as a computer including a processor 101, a memory 102, a storage 103, a communication device 104, an input device (optional), a display device (optional), and a bus connecting these. Each of these devices operates using power supplied from a battery (not shown). In the following description, the term "device" can be interpreted as a circuit, device, unit, etc. The hardware configuration of the information processing device 10 may be configured to include one or more of the devices shown in FIG. 3, or may be configured without including some of the devices. Furthermore, the information processing device 10 may be configured by communicating and connecting multiple devices each having a different housing.

[0028] Each function of the information processing device 10 is realized by loading specified software (programs) onto hardware such as the processor 101, memory 102, etc., so that the processor 101 performs calculations, controls communication via the communication device 104, and controls at least one of reading and writing data in the memory 102 and storage 103.

[0029] The processor 101 controls the entire computer by running, for example, an operating system. The processor 101 may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc. Furthermore, for example, a baseband signal processing unit, a call processing unit, etc. may be realized by the processor 101.

[0030] The processor 101 reads programs (program codes), software modules, data, etc. from at least one of the storage 103 and the communication device 104 into the memory 102 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described below. The functional blocks of the information processing device 10 may be implemented by a control program stored in the memory 102 and running on the processor 101. Various processes may be executed by one processor 101, or may be executed simultaneously or sequentially by two or more processors 101. The processor 101 may be implemented by one or more chips. The programs may be transmitted to the information processing device 10 via a telecommunications line.

[0031] The memory 102 is a computer-readable recording medium and may be configured by at least one of, for example, a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 102 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 102 can store executable programs (program codes), software modules, etc. for implementing the method according to this embodiment.

[0032] Storage 103 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 103 may also be called an auxiliary storage device.

[0033] The communication device 104 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also called, for example, a network device, a network controller, a network card, or a communication module.

[0034] Each device, such as the processor 101 and the memory 102, is connected by a bus for communicating information. The bus may be configured using a single bus, or different buses may be used between each device.

[0035] The information processing device 10 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 101 may be implemented using at least one of these pieces of hardware.

[0036] In this example, the programs stored in the storage 103 include a program (hereinafter referred to as a "server program") for causing a computer to function as a server in the information processing system 1. When the processor 101 is executing the server program, the processor 101, the memory 102, the storage 103, and the communication device 104 are examples of functional blocks for operating the information processing device 10. The processor 101 is an example of a first acquisition unit 11, a second acquisition unit 12, a first calculation unit 14, a second calculation unit 15, a personality estimation unit 16, an information generation unit 17, and a control unit 192. At least one of the memory 102 and the storage 103 is an example of a storage unit 191. The communication device 104 is an example of a first acquisition unit 11, a second acquisition unit 12, and an output unit 13.

[0037] Although detailed description will be omitted, the user terminal 20 is a computer having a processor, memory, storage, a communication device, an input device, and an output device, specifically, for example, a smartphone, a tablet terminal, or a personal computer. In this example, the programs stored in the storage of the user terminal 20 include a program (hereinafter referred to as a "client program") for causing the computer to function as a client in the information processing system 1. The configuration of the information processing system 1 has been described above. Next, the operation of the information processing system 1 will be described.

[0038] 2. Operation FIG. 4 is a sequence chart illustrating an example of an outline of the operation of the information processing system 1. Here, the overall processing by each device in the information processing system 1 will be described. In step S101, the information processing device 10 acquires an output request from the response terminal 30. In the subsequent sequence, this output request triggers processing. The response terminal 30 issues a request for output information to the information processing device 10 in response to, for example, an operation by a responder. If the responder is scheduled to respond to the target user in advance, the responder inputs information about the target user via the response terminal 30. The output request from the response terminal 30 includes at least the identification information of the target user.

[0039] In step S102, the information processing device 10 makes a data request for generating output information about the target user to the information collecting server 40. The data request includes a request for various data about the target user and aggregated data about multiple users.

[0040] In step S103, the information collecting server 40 reads various data from the database in response to the data request from the information processing device 10. Here, the database that manages user information will be described.

[0041] FIG. 5 is a diagram illustrating a user database 1000. In this example, the user database 1000 includes multiple records related to information acquired from the user terminal 20. Each record corresponds to information for each user, including the target user. Each record includes a user ID (terminal ID) and service-related information (contract information and behavioral history). The user ID (terminal ID) is identification information unique to each user. The service-related information is information acquired from the user terminal 20. The service-related information is subdivided into contract information and behavioral history. The contract information is information related to the contract status of the user terminal 20. When a user and a communication carrier enter into a contract for a communication line, for example, the contract terms include various conditions. The conditions include, for example, a contract plan or contract options. The information collection server 40 acquires this information from the user terminal 20 as contract information and records it in a database. The behavioral information is information that digitizes the user's behavioral results as the history of the user terminal 20. The behavioral information includes, for example, surveys, app logs, smartphone logs, and location information. The survey includes the aggregated results of a web survey or a physical survey conducted by a telecommunications carrier for multiple users. The application log includes a history of applications installed on the user terminal 20. The smartphone log includes a log of the times when the user terminal 20 was powered on and off. For example, the information collection server 40 can calculate the user's usage time of the user terminal 20 based on the smartphone log and generate features. The location information includes information indicating the location using a GPS (Global Positioning System) or the like. Various categories of behavioral information store data files of various formats. The information collection server 40 pre-sets data categories to be recorded as behavioral history. The information collection server 40 then arbitrarily acquires data corresponding to those categories from the user terminal 20. The information collection server 40 may add identifiers or the like to these data and manage them uniquely. The information collection server 40 uniquely manages the data of multiple user terminals 20 (multiple users) belonging to the information processing system 1.

[0042] The information collecting server 40 periodically collects data from the user terminal 20. The information collecting server 40 collects service-related information (specifically, contract information and behavioral history) from the user terminal 20. For example, the information collecting server 40 collects data from the user terminal 20 using web access, data synchronization, or an API (Application Programming Interface). The information collecting server 40 collects operation history, input history, access history, and the like from the user terminal 20. This process allows the information collecting server 40 to communicate data with the user terminal 20 over a network and accumulate various data. The data managed by the information collecting server 40 may also include analysis results of aggregated data for the target user and multiple users.

[0043] In step S104, the information processing device 10 acquires various data related to the target user and aggregated data related to multiple users. Note that these data may include analysis results by the information collecting server 40.

[0044] In step S105, the information processing device 10 acquires a first score for the target user. The information processing device 10 acquires the first score by calculation. The information processing device 10 calculates the first score indicating the level of IT literacy of the target user based on data acquired from the information collecting server 40. A specific example of the calculation method will be described later.

[0045] In step S106, the information processing device 10 acquires a second score for the target user. The information processing device 10 acquires the second score by calculation. As with the first score, the information processing device 10 calculates the second score indicating the target user's preferred type of response based on data acquired from the information collecting server 40. A specific example of a method for calculating the second score will also be described later.

[0046] In step S107, the information processing device 10 acquires output information corresponding to the first score and the second score. The output information includes first information corresponding to the first score and / or second information corresponding to the second score. Here, the output information (first information and second information) will be described.

[0047] FIG. 6 is a diagram illustrating an example of first information 1001. FIG. 6 is a schematic diagram of the final output related to the first information. The first information 1001 is composed of fields F11 and F12. Field F11 is a field that displays a first score. The first score indicates the target user's level of IT literacy (web utilization). In this example, the first score is a numerical value that indicates which level the target user is positioned in when classified into five grades. Here, it is defined that the lower the first score (the closer the numerical value is to 1), the lower the IT literacy, and the higher the first score (the closer the numerical value is to 5), the higher the IT literacy. In the first information 1001 shown in the figure, for example, the first score is "3," indicating that the target user's IT literacy is at a medium level. Field F12 is a field that displays a template corresponding to the first score. A preset sentence is entered in this field for each first score. This template includes a sentence explaining the target user's level of web utilization. Alternatively, the template may include information for improving the quality of service provided to the target user, advice for the service provider, etc. Additionally, the first information 1001 may include title information, user information, data update information, etc. in a predetermined format. Next, the second information will be described.

[0048] FIG. 7 is a diagram illustrating an example of second information 2001. Similar to FIG. 6, FIG. 7 is a schematic diagram of the final output related to the second information. The second information 2001 includes, for example, fields F21 and F22 in a predetermined format. Field F21 is a field displaying a second score. The second score is a numerical value indicating the target user's preferred type of service (whether polite or concise). Like the first score, the second score is divided into, for example, five grades. In this case, it is predefined that the lower the second score (the closer the numerical value is to 1), the more polite the user prefers service, and the higher the second score (the closer the numerical value is to 5), the more concise the user prefers service. In the second information 2001 shown in the figure, for example, the second score is "4," which presumably indicates that the target user prefers more concise service. Field F22 is a field displaying a template corresponding to the second score. A preset sentence is entered in this field for each second score. This template includes a sentence that describes the type of service preferred by the target user. Similarly to the first information, the template also includes advice for the agent to improve the quality of service provided to the target user. Additionally, the second information 2001 may include title information, user information, data update information, or the like, in a predetermined format.

[0049] Returning to FIG. 4 , in step S108, the information processing device 10 outputs the first information and the second information regarding the target user to the answering terminal 30. The answering terminal 30 acquires a data file including the predetermined format described in FIGS. 6 and 7 . Alternatively, the output information may include a format that reflects a combination of the first information 1001 and the second information 2001. In this case, the answering terminal 30 acquires data according to a format specified by the answering person or set in the information processing device 10. The answering terminal 30 presents the output information to the answering person in accordance with a predetermined UI (User Interface).

[0050] As described above, based on the first information and the second information, the information processing device 10 can provide support to the attendant to improve the quality of the service provided to the target user. Subsequently, in Sections 2-1 and 2-2, specific examples of calculation methods for each score will be described.

[0051] 2-1. Method of Calculating the First Score FIG. 8 is a flowchart illustrating a method of calculating the first score in the information processing system 1. The flow in FIG. 8 shows details of the processing of step S105 in FIG. 4. The following flow represents processing executed mainly by the information processing device 10. In step S11, the information processing device 10 acquires the behavioral history of the target user. The information processing device 10 cooperates with the information collection server 40, refers to the user database 1000, and reads out data of the target user included in the output request of the response terminal 30. The user database 1000 stores, by category, a history of the behaviors that the target user has performed via their own terminal. The information processing device 10 acquires information necessary for calculating the first score from this data. Specifically, the process is as follows.

[0052] In step S12, the information processing device 10 refers to the first score database. In this example, the information processing device 10 can identify data involved in the calculation of the first score from among the data stored in the user database 1000 by comparing it with the first score database. Here, a specific example of the first score database will be described.

[0053] FIG. 9 is a diagram illustrating the first score database 1002. In this example, the first score database 1002 includes multiple records related to information such as parameters (variables) required for calculating the first score. Each record corresponds to information for each behavioral history indicating the level of IT literacy. Each record includes a difficulty score, behavioral history, execution frequency score, data reference period, and notes. The difficulty score is a numerical value (grade) indicating the level of IT literacy. Essentially, this difficulty score is the primary component used to calculate the first score. The first score database 1002 is arranged in descending order of difficulty score (5 to 0) from top to bottom as a database layout. Note that a difficulty score of 0 corresponds to a case where there is no user behavioral history or insufficient data has been accumulated for score determination. The behavioral history is a list of user behaviors that are used to calculate the first score. The behavioral history to be calculated is preset by an administrator of the information processing system 1, for example. Furthermore, scores corresponding to each behavioral history are also preset. The execution frequency score is one of the components used to calculate the first score. The execution frequency score is used to adjust the difficulty score. Specific calculation formulas will be described later. The data reference period is information that specifies the period of the user's behavioral history that is the subject of calculation of the first score. For example, if the behavioral history indicates a data reference period of three years, only data from the user's behavioral history for the past three years from the present is subject to calculation. The remarks are information that indicates the content of the behavioral history. Note that the information processing device 10 may add an identifier or the like to the behavioral history and manage it uniquely. Alternatively, the information processing device 10 may record an identifier (or conditions, etc.) of data corresponding to the behavioral history. This enables the information processing device 10 to identify data corresponding to the behavioral history from the data acquired from the user terminal 20.

[0054] Returning to FIG. 8 , in step S13, the information processing device 10 calculates a first score. The information processing device 10 compares the behavioral history of the target user acquired from the user database 1000 with the first score database 1002. The information processing device 10 calculates the first score using a predetermined calculation method. For example, the first score S1 is calculated based on the behavioral history of the target user using the following formula (1):

[0055] In this example, "D max " represents the maximum difficulty score among the behavioral histories of the target user. For example, if there is even one behavioral history that indicates a difficulty score of "5" among the behavioral histories of the target user, D max The numerical value of is 5. max " represents the implementation frequency score corresponding to that behavioral history. "N" represents the number of times the target user performed that behavioral history. "D1" represents a numerical value (i.e., "1") corresponding to a behavioral history with a difficulty score of "1". "F1" indicates the implementation frequency score corresponding to that behavioral history. "n" represents the number of times the target user performed that behavioral history.

[0056] According to the above-described formula (1), the first score is determined according to the behavioral history with the highest difficulty score. In the simplest process, the information processing device 10 may identify the difficulty score of the behavioral history with the highest difficulty score among the behavioral history of the target user as the first score. However, if there is even one behavioral history with a difficulty score of "1," the first score needs to be adjusted to decrease using formula (1). Therefore, the information processing device 10 may first perform calculation processing according to whether there is any behavioral history with a difficulty score of "1" among the behavioral history of the target user.

[0057] Note that while Equation (1) can be considered a weighted average adjusted based on the behavioral history with the maximum difficulty score, it is designed so that the first score ultimately matches the maximum difficulty score (unless the difficulty score is "1"). Therefore, Equation (1) may be modified in various ways using the difficulty score and the performance frequency score. For example, it may be modified to include behavioral history corresponding to a difficulty score other than the maximum difficulty score.

[0058] In step S14, the information processing device 10 acquires first information corresponding to the first score. Here, the first information will be described.

[0059] FIG. 10 is a diagram illustrating a first information list 1003. In this example, the first information list 1003 is a list of first information corresponding to a first score. Like the difficulty score, the first score is a numerical value (grade) ranging from 0 to 5 indicating the level of IT literacy. The first information list 1003 is arranged in descending order of difficulty score (5 to 0) from top to bottom. The explanation (first information) is support information for the responder regarding the level of IT literacy of the user corresponding to the first score, in this case, the degree of web channel utilization. Each piece of first information is recorded in advance in a database or the like as a standard phrase. These sentences preferably include information that allows the responder to appropriately change the response depending on the first score. Note that first information corresponding to a first score of 0 may be information indicating that the user has no behavioral history or that insufficient data has been accumulated to determine the score.

[0060] As a result, the information processing device 10 can acquire the first score and the first information. This allows the information processing device 10 to output the first score and the first information from the target user's output information request at the response terminal 30. When outputting, the information processing device 10 uses a format such as the first information 1001 to output to the response terminal 30. This allows the respondent to (A) obtain advice on how to improve the quality of their response to the target user regarding their level of IT literacy. Next, a method for calculating (B) the second score regarding the user's preferred response type will be described.

[0061] 2-2. Method of Calculating the Second Score FIG. 11 is a flowchart illustrating a method of calculating the second score in the information processing system 1. The process in FIG. 11 shows details of the process of step S106 in FIG. 4. The following flow represents a process mainly executed by the information processing device 10. In step S21, the information processing device 10 cooperates with the information collection server 40 to read the user database 1000 and acquire service-related information of the target user. The service-related information is used to estimate the personality of the target user when calculating the second score. The information processing device 10 refers to the user database 1000 and reads data of the target user included in the output request of the response terminal 30.

[0062] In step S22, the information processing device 10 estimates the user's personality based on the service-related information. The service-related information and AI are used to estimate the user's personality. Regarding AI, the information processing device 10 estimates the user's personality using, for example, a trained machine learning model (hereinafter referred to as "machine learning model ML1"). Training the machine learning model ML1 uses, for example, training data in which the service-related information about the user is used as an explanatory variable and scores for each personality item are used as a response variable. Regarding the explanatory variables, the service-related information includes records of questionnaires completed by the user and various histories. These pieces of information reflect the user's personality. Regarding the response variable, the personality items represent generalized indicators of the user's personality. These indicators are predetermined in the information processing system 1. Furthermore, the information processing system 1 can assign scores (indexes) corresponding to each indicator. These scores are output as the response variable of the machine learning model ML1. As an example, the machine learning model ML1 includes a machine learning model such as a regression model, a linear regression model, or a nonlinear regression model.

[0063] The information processing device 10 can use the machine learning model ML1 to obtain scores for each item of multiple users, including the target user, in the user database 1000. In this example, an item is one of the parameters involved in calculating the second score. Here, a specific example of an item will be described.

[0064] FIG. 12 is a diagram illustrating an example of the item database 2002. In this example, the item database 2002 includes multiple records related to the scores of items required for calculating the second score. Each record corresponds to information for each user. Each record includes a user ID and an item. The user ID is identification information unique to each user. The user ID includes an identifier shared with the user database 1000. The items include item A and item B. Here, the second score primarily indicates the user's preferred type of service (whether they prefer more polite or more concise service), and therefore is highly dependent on the user's personality. In this invention, among the elements that contribute to the user's personality, an element based on the user's behavioral history is defined as item A, and an element based on the user's personality classification is defined as item B. Both of these items are information that reflect the personality of the target user. Item A includes, for example, a pack score related to a pack (such as a fee pack or a guarantee pack) included in a line contract, a model score related to the terminal model, etc. Item B is one of five personality categories represented by the so-called Big Five, such as openness, conscientiousness, extroversion, agreeableness, and emotional instability. FIG. 12 reflects the scores calculated by the machine learning model ML1 for items A and B based on service-related information. The correspondence between each item and service-related information is determined based on a predetermined identifier or the learning results of the machine learning model ML1. The information processing device 10 may calculate the scores at any timing and may freely manage the updating and deletion of the scores.

[0065] Returning to FIG. 11 , in step S23, the information processing device 10 acquires reference values ​​for multiple users. In this example, the reference values ​​are, for example, numerical values ​​that serve as a reference for each item corresponding to the user's personality, for factors related to the user's preferred type of response (whether the user prefers more polite or more concise). The factors referred to here refer to, for example, each individual personality attributed to the user's tendency to prefer which type of response. Here, the reference values ​​and factors will be described in detail.

[0066] FIG. 13 is a diagram illustrating a reference value list 2003. In this example, the reference value list 2003 is a matrix of each item and its corresponding reference value. Each factor is related to the user's preferred type of customer service. The numerical range of the reference value is preset. For example, the reference values ​​are specified in the range of "-1 to 1" (the so-called correlation coefficient range) from smallest to largest. In this example, the larger the absolute value of the factor (reference value) for each item, the higher the contribution to that factor. For example, taking the tendency of factor 0 as an example, for item A, the pack score is slightly "+" and the model score is slightly "-". This indicates that the user's behavior tends to be to take good care of the model. Furthermore, for item B, conscientiousness is significantly "+" and emotional instability is significantly "-". This indicates that the user's personality tends to be serious, polite, and calm and collected. Therefore, in this example, factor 0 is interpreted as a factor related to "likely preferring polite service." That is, here, Factor 0 is particularly defined as the factor linked to the second score. Note that Factor 1 is a reference factor related to "seems talkative (especially about new things)." In this embodiment, the final second score is calculated based on Factor 0, so a specific interpretation of Factor 1 will be omitted.

[0067] In the field of so-called factor analysis, a method is used to determine the reference values ​​of the reference value list 2003 based on the item database 2002. Factor analysis is a statistical data analysis method that reveals factors (e.g., preferred types of customer service) that are thought to lie behind numerous results (e.g., a user's personality). In this example, the inventors have noticed that when identifying a target user's preferred types of customer service, a relatively accurate analysis can be performed by finding a correlation with the personality estimated by machine learning. For example, the reference value for each item of factor 0 in FIG. 13 is calculated using the following equation (2), which shows a determinant:

[0068] In this example, "R" represents the correlation coefficient matrix corresponding to the data in the item database 2002. "A" represents the factor loading matrix as shown in FIG. -T " represents a transposed matrix. In other words, according to formula (2), the information processing device 10 can generate a factor loading matrix A ( FIG. 13 ) based on a correlation coefficient matrix R (not shown) corresponding to the item database 2002. The names "correlation coefficient matrix," "factor loading matrix," and "transposed matrix" are assigned to the data of this system in accordance with the determinants typically used in factor analysis.

[0069] Returning to FIG. 11 , in step S24, the information processing device 10 identifies the target user's preferred response type. The specific processing is divided into the following two stages. In the first stage, the information processing device 10 calculates the target user's factor score based on the reference value list 2003 that serves as a reference. The factor score is a numerical value corresponding to the reference value with respect to the target user's tendency for factor 0. For example, the factor score is calculated using the following equation (3) that shows a determinant.

[0070] In this example, "X" represents a matrix in the item database 2002. "A" represents a factor loading matrix in the reference value list 2003. "f" is a vector representing factor scores. Here, the factor scores will be explained.

[0071] FIG. 14 is a diagram illustrating an example of factor scores 2004. In this example, the factor scores 2004 are a list of user factor scores obtained by equation (3). The user ID is identification information for each user that is common to various databases. Here, multiple users other than the target user are also represented in the database. The factor scores (second scores) are numerical values ​​of the factor scores corresponding to each factor. Here, the numerical range of the factor scores is specified, for example, from the smallest to the largest, in the range of "-1 to 1," similar to the numerical range of the reference values ​​of the factors. In this example, the second scores are calculated as scores corresponding to the factor scores divided into five levels (for example, in increments of 0.4).

[0072] Returning to FIG. 11 , in step S25, the information processing device 10 acquires second information corresponding to the second score. As described above, the information processing device 10 acquires the second score based on the factor scores. The second score is linked to the second information. Here, the second information will be described.

[0073] FIG. 15 is a diagram illustrating a second information list 2005. In this example, the second information list 2005, like the first information list 1003, is a list of second information corresponding to the second score. The second information list 2005 is arranged in descending order of difficulty score (5 to 1) from top to bottom. The explanation (second information) is support information for the user based on the user's preferred type of interaction corresponding to the second score, i.e., whether the user prefers polite or concise interaction. Each piece of second information is pre-recorded in a database or the like as a standard phrase. These phrases include information that allows the user to appropriately change their interaction (whether polite or concise) depending on the second score. For example, the second information may include information indicating the target user's tendencies, the amount of communication, or a specific interaction technique.

[0074] As a result, the information processing device 10 can acquire the second score and the second information. In addition to the first score and the first information described in Section 2-1, the information processing device 10 outputs the output information of the target user to the answering terminal 30. When outputting, the information processing device 10 uses a predetermined format represented by the first information 1001 and the second information 2001 to output to the answering terminal 30. This allows the answering person to obtain advice for improving the quality of the answering provided to the target user regarding (A) the level of IT literacy and (B) the user's preferred answering type.

[0075] 3. Modifications The present invention is not limited to the above-described embodiment, and various modifications are possible. Some modifications will be described below. Two or more of the following features may be combined and applied.

[0076] (1) Information Processing System 1 The hardware configuration and network configuration of the information processing system 1 are not limited to those exemplified in the embodiment. The information processing system 1 may have any hardware configuration and network configuration as long as the required functions can be realized. For example, multiple physical devices may work together to function as the information processing system 1. For example, at least a portion of the information processing device 10 may be implemented in the customer service terminal 30. The customer service terminal 30 may acquire output information customized for each store or each customer service person. At least a portion of the information collection server 40 may be implemented in the information processing device 10.

[0077] (2) Information Processing Device 10 Some of the functions of the information processing device 10 may be implemented on another server. This server may be, for example, a physical server or a virtual server (including a so-called cloud). Furthermore, the correspondence between functional elements and hardware is not limited to that illustrated in the embodiment. For example, in the embodiment, at least some of the functions described as being implemented on the information processing device 10 may be implemented on another device or system, or conversely, at least some of the functions described as being implemented on another device or system may be implemented on the information processing device 10. In this example, the user terminal 20 may have at least some of the functions of the information processing device 10. In this case, the user terminal 20 may acquire service-related information of multiple users of the information processing device 10 and generate scores and output information for the target user who owns the user terminal. In this case, the user terminal 20 may generate the output information using any information acquired from the target user. The user terminal 20 may acquire user information by, for example, using an API (Application Programming Interface), website tracking, cookies, or the like.

[0078] (3) User Terminal 20 The user terminal 20 is not limited to the one exemplified in the embodiment. The user terminal 20 may perform the above-described processing using any display screen, input device, or various UIs. The user terminal 20 may be equipped with a function for acquiring user information using various sensors, devices, equipment, or applications (or web browsers) within the terminal. In this example, the user terminal 20 may be equipped with various sensors and may acquire information about the target user (output to the information processing device 10) using these sensors. The sensors include, for example, an acceleration or angular velocity sensor, a Global Navigation Satellite System (GNSS), a Light Detection and Ranging (LiDAR), or an Inertial Measurement Unit (IMU).

[0079] (4) Response Terminal 30 The response terminal 30 is not limited to the one exemplified in the embodiment. The response terminal 30 may have any functional configuration as long as it can realize the required functions or operations. The response terminal 30 does not have to be included in the information processing system 1. The response terminal 30 may have a function to collect user information from the user terminal 20. In this case, the response terminal 30 outputs the collected information to the information processing device 10.

[0080] (5) Overview of Operation The sequence chart shown in FIG. 4 merely shows one example of the operation, and the operation of the information processing system 1 is not limited to this. Some of the illustrated operations may be changed or omitted, the order may be changed, or new operations may be added. As a premise, when the information collecting server 40 acquires various data from the user terminal 20, it performs processing after obtaining the user's consent. The information collecting server 40 may automatically acquire data from the user terminal 20. The output request from the response terminal 30 in step S101 may be omitted. The processes of steps S105 to S107 may be performed at any timing. In step S108, the information processing device 10 may output output information in any format.

[0081] In step S108, the information processing device 10 may output output information that is a combination of the first score and the second score. In this example, the information processing device 10 may add two classification labels to the first score, indicating whether the IT literacy is high or low (for example, "high" if 5 or higher, and "low" if 1 or lower). Similarly, two classification labels, indicating whether the second score is concise or polite (for example, "concise" if 5 or higher, and "polite" if 1 or lower), may be added. According to such classification, the following four new patterns of output are obtained as types of output information.

[0082] For example, if the target user indicates a combination of "high first score" and "concise second score," the output information may include information that more succinctly emphasizes the ability to complete procedures via a web channel or the like, while highlighting the key points. If the target user indicates a combination of "high first score" and "thorough second score," the output information may include information that more specifically emphasizes the ability to complete procedures online via a web channel or the like (including important points, etc.). The output information may also include information that conveys more advanced content (not just instructions on how to use the product, but also additional features, etc.). If the target user indicates a combination of "low first score" and "thorough second score," the output information may include information that more succinctly emphasizes the ability to complete procedures in a store (offline), while highlighting the key points. If the target user indicates a combination of "low first score" and "thorough second score," the output information may include information that more specifically emphasizes the ability to complete procedures in a store (offline), while highlighting the key points.

[0083] (6) Method for Calculating the First Score The flowchart shown in FIG. 8 merely illustrates one example of the operation, and the method for calculating the first score in the information processing system 1 is not limited to this. Some of the illustrated operations may be changed or omitted, the order may be changed, or new operations may be added. In step S13, the information processing device 10 may calculate the first score by any method. Equation (1) is merely a representative calculation formula, and any calculation formula or arithmetic formula may be used to calculate the first score. The first score may be a calculation result that includes various parameters in addition to the difficulty score and the execution frequency score. In step S14, the information processing device 10 may calculate the first information by any method. The first information does not need to be a fixed phrase, and may be information that is generated each time depending on the first score of the target user.

[0084] (7) Method for Calculating the Second Score The flowchart shown in FIG. 11 merely illustrates an example of the operation, and the method for calculating the second score in the information processing system 1 is not limited thereto. Some of the illustrated operations may be changed or omitted, the order may be changed, or new operations may be added. The processes of steps S22 to S24 may be integrated using machine learning model ML1. In step S22, the information processing device 10 may calculate the score for each item in any way. In step S23, the information processing device 10 may generate a reference value based on at least some of the multiple users. In this example, the factors may include not only factor 0, which relates to "likes to be polite," but also factor 1, which relates to "likes to talk (especially about new things)." In this case, the second score may be calculated based on factor 1. For example, the information processing device 10 may generate a second score and second information according to the interaction type, including whether or not to engage in casual conversation, linked to factor 1, in addition to or instead of the interaction type, i.e., whether or not the interaction type is concise or polite. Note that Equation (2) or Equation (3) is merely a representative calculation formula, and any calculation formula or arithmetic formula may be used to calculate the second score. Furthermore, since the second score includes information about the user's personality, the present embodiment uses a factor analysis method, but any statistical method may actually be adopted. The information processing device 10 may use an index such as the MBTI (Myers-Briggs Type Indicator) in addition to or instead of the BigFive personality classification. Furthermore, the interpretation of each factor is not limited to the example of the embodiment, and may be interpreted in any way.

[0085] (8) Database (Data) The databases (or the data itself) of the information processing system 1 shown in FIGS. 5, 6, 7, 9, 10, and 12 to 15 are not limited to those exemplified in the embodiments. In this example, any data may be registered in the database. The user database 1000 may record any data as long as it is information related to users. For example, service-related information may include user reviews of the service.

[0086] (9) Others The various programs executed by the processor 101 may be provided by downloading via a network such as the Internet, or may be provided in a state recorded on a computer-readable non-transitory recording medium such as a DVD-ROM. Each processor may be, for example, a CPU, an MPU (Micro Processing Unit), or a GPU (Graphics Processing Unit).

[0087] The block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of hardware and / or software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (e.g., wired, wireless, etc.) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

[0088] Functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0089] For example, the information processing device 10 according to an embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure.

[0090] Each aspect or embodiment described in the present disclosure may be applied to at least one of systems using LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), FRA (Future Radio Access), NR (New Radio), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, UWB (Ultra-Wide Band), Bluetooth (registered trademark), or other suitable systems, and next-generation systems enhanced based on these. Furthermore, a combination of multiple systems (e.g., a combination of at least one of LTE and LTE-A with 5G) may also be applied.

[0091] The order of the procedures, sequences, sequence charts, etc. of each aspect or embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order and are not limited to the particular order presented.

[0092] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0093] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0094] 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 herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0095] Software, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise, should be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc. Additionally, software, instructions, information, etc. may be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then such wired and / or wireless technologies are included within the definition of a transmission medium.

[0096] 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 be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof. Note that terms described in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings.

[0097] Furthermore, the information, parameters, etc. described in this disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information.

[0098] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0099] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0100] The "unit" in the configuration of each of the above devices may be replaced with "means," "circuit," "device," or the like.

[0101] When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0102] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0103] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0104] 1...information processing system, 10...information processing device, 20...user terminal, 30...response terminal, 40...information collection server, 9...network, 11...first acquisition unit, 12...second acquisition unit, 13...output unit, 14...first calculation unit, 15...second calculation unit, 16...personality estimation unit, 17...information generation unit, 191...storage unit, 192...control unit, 101...processor, 102...memory, 103...storage, 104...communication device, 1000...user database, 1001...first information, 1002...first score database, 1003...first information list, 2001...second information, 2002...item database, 2003...reference value list, 2004...factor score, 2005...second information list, F...field, ML...machine learning model, U...user

Claims

1. An information processing device having: a first acquisition unit that acquires a first score that indicates the level of IT literacy of a user, calculated based on a first history that indicates the user's history of using a service; a second acquisition unit that acquires a second score that indicates the user's preferred type of response, calculated based on an estimation of the user's personality; and an output unit that outputs information corresponding to the first score and the second score.

2. An information processing device as described in claim 1, further comprising a calculation unit that calculates the second score using service-related information regarding the service used by the user using a mobile terminal and AI, and the second acquisition unit acquires the second score from the calculation unit.

3. The information processing device according to claim 2, wherein the service-related information includes a usage history of applications installed on the mobile terminal by the user.

4. The information processing device according to claim 2, wherein the service-related information includes a usage history of the mobile terminal by the user.

5. The information processing device according to claim 2, wherein the service-related information includes a history of location information of the mobile terminal.

6. The information processing device according to claim 2, wherein the service-related information includes subscriber information for mobile communications using the mobile terminal.

7. The information processing device according to claim 2, wherein the AI ​​includes a trained model trained using training data in which the service-related information about a plurality of users is used as an explanatory variable and scores obtained from the results of a personality assessment questionnaire administered to the plurality of users are used as a target variable.

8. An information processing method comprising the steps of: acquiring a first score indicating the level of the user's IT literacy, calculated based on a first history indicating the user's history of using a service; acquiring a second score indicating the user's preferred type of response, calculated based on an estimation of the user's personality; and outputting information corresponding to the first score and the second score.

Images