End-of-life planning support system, end-of-life planning support method, and program

Abstract

To improve user convenience.SOLUTION: An end-of-life planning support system (1) comprises a user characteristic information acquisition unit (101) and an end-of-life planning support unit (102). The user characteristic information acquisition unit acquires user characteristic information regarding characteristics according to the user's web service usage. The end-of-life planning support unit supports the end-of-life planning, which is an activity for preparing the end-of-life, based on the user characteristic information.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to an end-of-life planning support system, an end-of-life planning support method, and a program. [Background technology]

[0002] Conventionally, activities for preparing for the end of life have been carried out. For example, Patent Document 1 describes an information processing device that collects information about a user acquired from the user's terminal, generates questions for the user based on the collected information about the user, and outputs options for the user's future actions based on the answers to the questions, thereby providing support for preparing for the end of life.

[0003] For example, Patent Document 2 describes an end-of-life note creation support system that receives the usage history of a user's information terminal, obtains usage information necessary to create an end-of-life note from the collected or acquired usage history, analyzes the acquired usage information, automatically creates an end-of-life note template based on the analysis results of the usage information analysis unit, and presents the end-of-life note template to the user regularly or irregularly via the information terminal.

[0004] For example, Patent Document 3 describes an ending note management system that includes an ending note database for managing customers' ending notes, an ending note correction means, an ending note registration means, an ending note execution means, and a customer status safety confirmation means. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2023-112567 [Patent Document 2] Patent Publication No. 2021-174451 [Patent Document 3] Patent Publication No. 2021-174011 Summary of the Invention [Problem to be solved by the invention]

[0006] However, while the technologies of Patent Documents 1 and 2 can provide end-of-life support based on information indicating how a user uses a terminal, some of this information indicates user characteristics that are effective for end-of-life support, while other information is not very relevant. The technology of Patent Document 3 can manage an end-of-life note, but is not aimed at end-of-life support tailored to the user's characteristics. The technologies of Patent Documents 1 to 3 cannot provide effective end-of-life support tailored to the user's characteristics, and therefore cannot sufficiently improve user convenience.

[0007] One of the purposes of the present disclosure is to improve user convenience. [Means for solving the problem]

[0008] The end-of-life planning support system of the present disclosure includes a user characteristic information acquisition unit that acquires user characteristic information regarding characteristics according to the user's usage of web services, and an end-of-life planning support unit that provides end-of-life planning support related to end-of-life activities, which are activities leading up to the end of one's life, based on the user characteristic information. [Effects of the Invention]

[0009] The present disclosure can improve convenience for users. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of the hardware configuration of an end-of-life planning support system. [Figure 2] FIG. 10 is a diagram illustrating an example of a screen displayed on a user terminal. [Figure 3] FIG. 10 is a diagram illustrating an example of a screen displayed on a user terminal. [Figure 4]FIG. 1 is a diagram illustrating an example of a function realized by the end-of-life planning support system. [Figure 5] FIG. 2 is a diagram illustrating an example of a user database. [Figure 6] FIG. 10 is a diagram showing an example of end-of-life planning support data. [Figure 7] FIG. 10 is a diagram illustrating an example of processing executed in the end-of-life planning support system. [Figure 8] FIG. 10 is a diagram illustrating an example of a function realized in a modified example. [Figure 9] A figure showing an example of an end-of-life planning support screen in variant example 5. [Figure 10] A figure showing an example of an end-of-life planning support screen for variant example 6. DETAILED DESCRIPTION OF THE INVENTION

[0011] [1. Hardware configuration of the end-of-life support system] An example of an embodiment of an end-of-life planning support system, end-of-life planning support method, and program according to the present disclosure will be described. FIG. 1 is a diagram showing an example of the hardware configuration of an end-of-life planning support system. For example, the end-of-life planning support system 1 includes a server 10 and a user terminal 20. Each of the server 10 and the user terminal 20 is connected to a network N such as the Internet or a LAN. In the example of FIG. 1, one server 10 and one user terminal 20 are shown, but there may be multiple servers 10 and multiple user terminals 20 at least.

[0012] The server 10 is a server computer. For example, the server 10 includes a control unit 11, a storage unit 12, and a communication unit 13. The control unit 11 includes at least one processor. The storage unit 12 includes at least one of a volatile memory such as RAM and a non-volatile memory such as a flash memory. The communication unit 13 includes at least one of a communication interface for wired communication and a communication interface for wireless communication.

[0013] The user terminal 20 is a user's computer. For example, the user terminal 20 is a smartphone, a tablet, a personal computer, or a wearable terminal. The user terminal 20 includes a control unit 21, a memory unit 22, a communication unit 23, an operation unit 24, and a display unit 25. The hardware configurations of the control unit 21, the memory unit 22, and the communication unit 23 may be similar to those of the control unit 11, the memory unit 12, and the communication unit 13, respectively. The operation unit 24 is an input device such as a touch panel or a mouse. The display unit 25 is a display such as a liquid crystal or organic EL display.

[0014] The program stored in the storage units 12, 22 may be supplied to the server 10 or the user terminal 20 via the network N. Also, at least one of a reading unit (e.g., a memory card slot) that reads a computer-readable information storage medium and an input / output unit (e.g., a USB port) that inputs and outputs data to and from an external device may be included in the server 10 or the user terminal 20. For example, a program stored in an information storage medium may be supplied to the server 10 or the user terminal 20 via at least one of the reading unit and the input / output unit.

[0015] Furthermore, the end-of-life planning support system 1 only needs to include at least one computer. The computers included in the end-of-life planning support system 1 are not limited to the example in Figure 1. For example, the end-of-life planning support system 1 may include only the server 10 and the user terminal 20. In this case, the server 10 and the user terminal 20 exist outside the end-of-life planning support system 1. The end-of-life planning support system 1 may only include the server 10. In this case, the user terminal 20 exists outside the end-of-life planning support system 1. For example, the end-of-life planning support system 1 may include the server 10 and other computers not shown in Figure 1.

[0016] [2. Overview of the End-of-Life Support System] In this embodiment, the end-of-life planning support system 1 provides an end-of-life planning support service to a user. The end-of-life planning support service is a service that supports a user in end-of-life planning. End-of-life planning is an activity to prepare for the end of one's life. End-of-life planning may have a known meaning. The activities carried out in end-of-life planning may also be various known activities. For example, as end-of-life planning, a user makes plans for sorting out belongings, sorting out assets, inheritance, medical care, nursing care, funerals, graves, work, housing, hobbies, or health.

[0017] For example, an end-of-life planning app, which is an application for an end-of-life planning support service, is installed on the user terminal 20. The user registers for the end-of-life planning support service from the end-of-life planning app on the user terminal 20 and uses the end-of-life planning support service. The user may also use the end-of-life planning support service from the browser on the user terminal 20 instead of the end-of-life planning app. For example, when the user starts up the user terminal 20, the user terminal 20 displays a menu screen showing the operating system menu on the display unit 25.

[0018] 2 and 3 are diagrams showing examples of screens displayed on the user terminal 20. As shown in the upper left of Fig. 2, the menu screen SC1 displays icons indicating various functions that the user can use from the user terminal 20. For example, icon I10 indicates an EC app, which is an application for an EC (electronic commerce) service. Icon I11 indicates an end-of-life planning app. The menu screen SC1 may also display icons for web services other than the EC service and end-of-life planning support service.

[0019] For example, when a user selects icon I10, the user terminal 20 launches an EC app and communicates with a computer of the EC service. As shown in the upper right corner of FIG. 2, the user terminal 20 displays an EC screen SC2 on the display unit 25. The user can use the EC service from the EC screen SC2. The flow of a user using the EC service may be similar to a known flow. For example, the user can search for products by entering any search criteria, purchase products added to the shopping cart using any payment method, and post information about the products they have purchased on a social networking site. The user may use the EC service from the browser of the user terminal 20 instead of the EC app.

[0020] For example, when a user selects icon I11, the user terminal 20 launches an end-of-life planning app and communicates with the server 10. As shown in the lower right of FIG. 2, the user terminal 20 displays an end-of-life planning support screen SC3 on the display unit 25. For example, the end-of-life planning support screen SC3 includes an array of buttons B30 that allow the user to use various functions provided by the end-of-life planning support service. The end-of-life planning support service provides various functions related to supporting the user in end-of-life planning. The user can use any function of the end-of-life planning support service from the end-of-life planning support screen SC3.

[0021] In this embodiment, an example is given in which a user uses a plan registration function to register various plans for end-of-life planning. For example, a user can select the "organization of belongings" button B30 to register a plan for organizing belongings in the end-of-life planning support service. A user can select the "inheritance" button B30 to register a plan for inheritance in the end-of-life planning support service. A user can select the "funeral / grave" button B30 to register a plan for at least one of a funeral and a grave in the end-of-life planning support service. A user can select the "work" button B30 to register a work plan in the end-of-life planning support service. A user can select the "residence" button B30 to register a plan for housing in the end-of-life planning support service.

[0022] Note that the functions available to users in the end-of-life planning support service are not limited to the plan registration function. The end-of-life planning support service may also provide other functions related to end-of-life planning support. For example, the end-of-life planning support service may also provide a function for supporting the creation of an end-of-life note, a function for matching users with financial planners or lawyers, a function for introducing users to insurance company services, a function for introducing users to financial institution services, a function for introducing users to travel reservation services, a function for accepting reservations from funeral companies, or other functions.

[0023] In this embodiment, users can, in principle, freely use the various functions provided by the end-of-life planning support service. However, users often lack prior knowledge about end-of-life planning and may not know where to start. Even if users try to obtain prior knowledge by searching websites related to end-of-life planning, such websites only contain general information, so users may not necessarily find information that suits them. It is believed that the end-of-life planning support that is effective for each user will vary depending on the user.

[0024] Therefore, the end-of-life planning support system 1 of this embodiment provides end-of-life planning support based on characteristics according to the user's usage of EC services. User characteristics can also be referred to as the user's features, classification, or attributes. Since the content of end-of-life planning support varies depending on the user, it is thought that the user's characteristics estimated from the usage of EC services also correlate with the content of end-of-life planning support. The end-of-life planning support system 1 provides end-of-life planning support according to the characteristics estimated from the EC services the user normally uses.

[0025] For example, a user who tends to post information about products sold through e-commerce services on social media is estimated to have an SNS characteristic that indicates that the user frequently uses SNS. When a user with an estimated SNS characteristic selects the "Arrangement of Belongings" button B30 on the end-of-life planning support screen SC3 shown in the upper left of Fig. 3, the user terminal 20 displays on the display unit 25 the end-of-life planning support screen SC3, as shown in the upper right of Fig. 3, with the "SNS Account" button B31 for arranging digital belongings such as SNS accounts placed first.

[0026] For example, for a user who tends to use a credit card to pay for e-commerce services, a card characteristic indicating that the user frequently uses a credit card is inferred. When a user whose card characteristic is inferred selects the "Arrangement of Belongings" button B30 on the end-of-life planning support screen SC3 in the upper left of Fig. 3, the user terminal 20 displays on the display unit 25 the end-of-life planning support screen SC3, as shown in the lower left of Fig. 3, with the "Credit Card" button B31 for arranging digital belongings such as credit card login accounts placed first.

[0027] For example, for a user who tends to use a bank account to pay for e-commerce services, a banking characteristic indicating that the user frequently uses a bank account is inferred. When a user with an inferred banking characteristic selects the "Arrangement of Belongings" button B30 on the end-of-life planning support screen SC3 in the upper left of Fig. 3, the user terminal 20 displays on the display unit 25 the end-of-life planning support screen SC3, which initially displays the "Bank Account" button B31 for arranging digital belongings such as online banking, as shown in the lower right of Fig. 3.

[0028] The end-of-life planning support system 1 may also support end-of-life planning other than estate sorting planning based on the user's characteristics. The subject of end-of-life planning support based on the user's characteristics is not limited to estate sorting. For example, the end-of-life planning support system 1 may also support asset sorting, inheritance, medical care, nursing care, funerals, graves, work, housing, hobbies, or health planning based on the user's characteristics. In this way, the end-of-life planning support system 1 of this embodiment increases user convenience by providing end-of-life planning support in the end-of-life planning support service based on the user's characteristics estimated from the usage status of the EC service. Details of the end-of-life planning support system 1 will be explained below.

[0029] [3. Functions realized by the end-of-life support system] FIG. 4 is a diagram showing an example of a function realized by the end-of-life planning support system 1.

[0030] [3-1. Functions realized by the server] For example, the server 10 includes a data storage unit 100, a user characteristic information acquisition unit 101, and an end-of-life planning support unit 102. The data storage unit 100 is realized by the storage unit 12. The user characteristic information acquisition unit 101 and the end-of-life planning support unit 102 are each realized by the control unit 11.

[0031] [Data storage section] The data storage unit 100 stores data necessary for the end-of-life planning support service. For example, the data storage unit 100 stores a user database DB and end-of-life planning support data DT.

[0032] FIG. 5 is a diagram showing an example of a user database DB. The user database DB is a database that stores various information related to users. For example, the user database DB stores a user ID, a password, user registration information, user characteristic information, and end-of-life planning content information. The user database DB may also store other information. For example, the user database DB may store usage history information related to the user's usage history of the end-of-life planning support service (e.g., login date and time). The server 10 updates the usage history information based on data received from the user terminal 20. For example, when a user logs in to the end-of-life planning support service, the server 10 updates the usage history information to indicate that the current date and time is the login date and time.

[0033] The user ID and password are information that the user uses to log in to the end-of-life planning support service. The user ID is an example of user identification information that can identify the user. In addition to the user ID, other information such as an email address or a telephone number may also be used as user identification information. In this embodiment, an example is given in which the user ID for the end-of-life planning support service and the user ID for the EC service are the same.

[0034] The user ID for the end-of-life planning support service and the user ID for the EC service may be different. If these user IDs are different, association data indicating the association between these user IDs is stored in the data storage unit 100 or elsewhere. The server 10 or another computer can identify which user has which user ID based on the association data.

[0035] The user registration information is information about a user who has registered with the end-of-life planning support service. The user registration information may be the user's personal information or the user's demographic information. For example, the user's name, date of birth, age, address, or a combination of these is registered with the end-of-life planning support service as the user registration information. The user registration information may be information registered with other services such as e-commerce services, or may be information entered by the user when registering to use the end-of-life planning support service.

[0036] The user characteristic information is information about the characteristics of a user. In this embodiment, multiple characteristics are prepared, and a user has at least one characteristic. The user characteristic information indicates at least one characteristic possessed by the user. Since a user may have multiple characteristics, the user characteristic information may indicate multiple characteristics. In the example of Figure 3, multiple characteristics such as SNS characteristics, card characteristics, and bank characteristics are prepared, and the user characteristic information indicates at least one characteristic of these multiple characteristics that is estimated to be possessed by the user. If no characteristics are estimated for the user, the user characteristic information indicates that no user characteristics have been estimated. The user characteristics are correlated with the content of end-of-life planning support that should be provided. The user characteristic information may be expressed by letters, numbers, symbols, or a combination thereof.

[0037] In this embodiment, the user's characteristics are estimated by a system other than the end-of-life planning support system 1. For example, the other system may be an EC service system, or may be a system different from the EC service. The other system estimates the user's characteristics based on the user's usage of the EC service and generates user characteristic information. The other system transmits the user's user characteristic information to the server 10. The server 10 stores the user characteristic information of the user received from the other system in the user database DB in association with the user ID of the user.

[0038] The method for estimating the user's characteristics may be a known method. For example, the other system acquires usage status data indicating the user's usage status based on the content of communication with the user terminal 20 of the user who used the EC service. The usage status data indicates the pages viewed by the user, the products or services bookmarked by the user, the products or services purchased by the user, or other information.

[0039] For example, the other system quantifies information included in the usage data of each of multiple users as needed (e.g., tallying the number of page views, the number of products or services bookmarked, or the number of products or services purchased), and then performs clustering of each user based on a predetermined clustering method. The clustering method may be a known method. For example, the clustering method may be DB-SCAN, k-means, hierarchical clustering, an unsupervised machine learning method, or another method. The other system performs clustering so that users with similar usage patterns belong to the same cluster. Each cluster corresponds to a user's characteristics. A person in charge of the other system assigns a name indicating the user's characteristics to each cluster as needed. The other system generates user characteristic information based on the results of the clustering.

[0040] In the example of FIG. 3, the usage data indicates information about products uploaded to the SNS and information about the payment method used by the user to pay for the EC service. Another system performs clustering on the usage data including this information, and clusters the users into a cluster of users who tend to upload product information to the SNS, a cluster of users who tend to use credit cards for the EC service, and a cluster of users who tend to use bank accounts for the EC service. Based on the results of the clustering, the other system identifies which users belong to which cluster and generates user characteristic information. The clusters are not limited to these examples. The clusters may be clusters that correspond to the information indicated by the usage data.

[0041] Note that the other system may estimate user characteristics using a method other than clustering. For example, the other system may acquire user characteristic information of a user based on a learning model that has learned the relationship between training user usage data and user characteristic information of the training user. The learning model is a model developed using a machine learning technique. Machine learning may be any of various known techniques. For example, machine learning may be a neural network, a support vector machine, a large-scale language model, or other techniques. The learning method may also be similar to a method adopted in known machine learning techniques. The other system inputs usage data of a user to be estimated into a trained learning model. The learning model calculates an embedded representation (e.g., a feature vector) of the usage data input to it based on parameters adjusted by learning, and outputs user characteristic information corresponding to the embedded representation. The other system acquires the user characteristic information output from the learning model.

[0042] The end-of-life planning content information is information regarding the content of end-of-life planning carried out by the user using the end-of-life planning support service. For example, the end-of-life planning content information indicates the content of the plan that the user registered with the end-of-life planning support service. In the examples of Figures 2 and 3, the end-of-life planning content information indicates the content of each of the following plans that the user has planned: sorting out belongings, inheritance, funeral, grave, work, and residence. The end-of-life planning content information may indicate a plan called an ending note. The end-of-life planning content information may also indicate someone to consult with, such as a lawyer or financial planner. The end-of-life planning content information may also indicate the content of other services used as part of end-of-life planning (for example, the details of a travel reservation made by the user using a travel reservation service, or the details of a product purchased by the user using an e-commerce service).

[0043] FIG. 6 is a diagram showing an example of end-of-life planning support data DT. The end-of-life planning support data DT is a database that stores information regarding the relationship between user characteristic information and the processing content of end-of-life planning support. In the example of FIG. 6, the end-of-life planning support data DT indicates the relationship between user characteristic information and end-of-life planning support information that indicates the processing content of end-of-life planning support. The end-of-life planning support data DT may be in any format. For example, the end-of-life planning support data DT may be in table format, mathematical formula format, part of code included in a program, a machine learning model, or other format.

[0044] In the example of FIG. 6, the end-of-life planning support information is the arrangement order of the buttons B31 on the end-of-life planning support screen SC3. For example, user characteristic information indicating SNS characteristics is associated with end-of-life planning support information indicating that the "SNS account" button B31 is to be arranged first. User characteristic information indicating card characteristics is associated with end-of-life planning support information indicating that the "credit card" button B31 is to be arranged first. User characteristic information indicating bank characteristics is associated with end-of-life planning support information indicating that the "bank account" button B31 is to be arranged first.

[0045] The end-of-life planning support information may indicate a layout other than the button B31 (for example, the layout of a user interface such as an input form). The end-of-life planning support information may indicate the type of information to be presented to the user, rather than the layout on the end-of-life planning support screen SC3. For example, user characteristic information indicating SNS characteristics may be associated with end-of-life planning support information indicating a link to a website that contains information on how to organize digital belongings related to SNS. User characteristic information indicating card characteristics may be associated with end-of-life planning support information indicating a link to a website that contains information on how to cancel a credit card. User characteristic information indicating bank characteristics may be associated with end-of-life planning support information indicating a link to a website that contains information on how to cancel a bank account.

[0046] The data stored in the data storage unit 100 is not limited to the above examples. The data storage unit 100 may store any data necessary for end-of-life planning support. For example, if the end-of-life planning support system 1, rather than another system, estimates the user's characteristics, the data storage unit 100 may store a program and data for estimating the user's characteristics. The data storage unit 100 may also store data (e.g., HTML data or image data) for displaying the end-of-life planning support screen SC3.

[0047] [User characteristic information acquisition section] The user characteristic information acquisition unit 101 acquires user characteristic information relating to characteristics according to the user's usage of the EC service. The EC service is an example of a web service. Therefore, the phrase "EC service" can be read as "web service." A web service is a service provided on the web (Internet or online). A web service can also be called an Internet service or an online service.

[0048] The web service may be a service other than an e-commerce service. The web service is not limited to an e-commerce service. For example, the web service may be a travel reservation service, a communication service, a payment service, a financial service, an online flea market service, a video distribution service, or another service. The end-of-life planning support service is also a type of web service. In this embodiment, the user characteristic information acquisition unit 101 acquires user characteristic information indicating characteristics according to the usage status of a web service (e.g., an e-commerce service) other than the end-of-life planning support service, rather than characteristics according to the usage status of the end-of-life planning support service. The user characteristic information acquisition unit 101 may also acquire user characteristic information indicating characteristics according to the usage status of the end-of-life planning support service.

[0049] Usage status is information indicating how an EC service is used. Usage status can also be referred to as the actions taken by a user in the EC service or the usage history of the EC service. For example, posts made by a user on social media or the like, pages viewed by a user, products bookmarked by a user, products purchased by a user, payment methods used by a user, or the time period during which a user logs in to the EC service correspond to the user's usage status. Usage status may be any information obtained from the content of communication with the user terminal 20 when a user uses a web service, such as an EC service.

[0050] In this embodiment, an example is taken of a case where user characteristic information has already been estimated and stored in a user database DB. Therefore, the user characteristic information acquisition unit 101 acquires the user characteristic information from the user database DB. If the user characteristic information is stored in a database other than the user database DB, the user characteristic information acquisition unit 101 acquires the user characteristic information from the other database. If the user characteristic information is stored in a computer or an external information storage medium other than the server 10, the user characteristic information acquisition unit 101 acquires the user characteristic information from the other computer or the external information storage medium.

[0051] The user's characteristics may be estimated by a known method. For example, the user characteristic information acquisition unit may acquire user characteristic information indicating user characteristics estimated by a technique called user profiling, which is used in behavioral analysis in web services. For example, the user characteristic information acquisition unit may acquire user characteristic information indicating user characteristics estimated by a technique for analyzing user behavior on social networking sites. For example, the user characteristic information acquisition unit may acquire user characteristic information indicating user characteristics estimated by an AI agent that understands user consumption behavior by analyzing big data in web services.

[0052] [End-of-life Support Department] The end-of-life planning support unit 102 provides support for end-of-life planning, which is activities for approaching the end of one's life, based on user characteristic information. End-of-life planning support means outputting information related to end-of-life planning to the user terminal 20 or executing information processing for that purpose. The end-of-life planning support unit 102 provides support for end-of-life planning by determining, from among multiple pieces of information related to end-of-life planning that can be presented to the user, based on user characteristic information, which information should be presented to the user, and determining the order in which the information should be presented to the user based on user identification information, and outputting the information to the user terminal 20.

[0053] In this embodiment, the relationship between the user characteristic information and the end-of-life planning support information is defined in the end-of-life planning support data DT, so the end-of-life planning support unit 102 acquires end-of-life planning support information associated with the user characteristic information acquired by the user characteristic information acquisition unit 101 based on the end-of-life planning support data DT, and provides end-of-life planning support based on the end-of-life planning support information. If the end-of-life planning support information indicates the content of information processing, the end-of-life planning support unit 102 executes the information processing indicated by the end-of-life planning support information. If the end-of-life planning support information indicates the type of information to be presented to the user, the end-of-life planning support unit 102 presents the type of information indicated by the end-of-life planning support information to the user.

[0054] 6, the order of buttons B31 on the end-of-life planning support screen SC3 is indicated as the end-of-life planning support information, so the end-of-life planning support unit 102 determines the arrangement of buttons B31 so that they are in the order indicated by the end-of-life planning support information, and displays the end-of-life planning support screen SC3 on the user terminal 20. For example, user characteristic information indicating SNS characteristics is associated with end-of-life planning support information indicating that the "SNS account" button B31 should be arranged first, so the end-of-life planning support unit 102 displays the end-of-life planning support screen SC3 on the user terminal 20, in which the "SNS account" button B31 is arranged first.

[0055] For example, since the user characteristic information indicating the card characteristics is associated with end-of-life planning support information indicating that the "Credit Card" button B31 should be placed first, the end-of-life planning support unit 102 causes the user terminal 20 to display the end-of-life planning support screen SC3 on which the "Credit Card" button B31 should be placed first. Since the user characteristic information indicating the bank characteristics is associated with end-of-life planning support information indicating that the "Bank Account" button B31 should be placed first, the end-of-life planning support unit 102 causes the user terminal 20 to display the end-of-life planning support screen SC3 on which the "Bank Account" button B31 should be placed first.

[0056] Note that, if the end-of-life planning support information indicates a layout other than button B31 (for example, the layout of a user interface such as an input form), the end-of-life planning support unit 102 may display an end-of-life planning support screen SC3 with the layout indicated in the end-of-life planning support information on the user terminal 20. In other words, the end-of-life planning support unit 102 may provide end-of-life planning support by displaying an end-of-life planning support screen SC3 with a layout according to the characteristics indicated by the user characteristic information on the user terminal 20.

[0057] For example, if the end-of-life planning support information indicates the type of information to be presented to the user, rather than the layout on the end-of-life planning support screen SC3, the end-of-life planning support unit 102 may provide the user with the type of information indicated in the end-of-life planning support information. For example, the end-of-life planning support unit 102 may provide end-of-life planning support to a user with an SNS characteristic by providing information summarizing how to organize SNS. The end-of-life planning support unit 102 may provide end-of-life planning support to a user with a card characteristic by providing information summarizing how to organize credit cards. The end-of-life planning support unit 102 may provide end-of-life planning support to a user with a bank characteristic by providing information summarizing how to organize bank accounts.

[0058] [3-2. Functions implemented on user devices] For example, the user terminal 20 includes a data storage unit 200, an operation reception unit 201, and a display control unit 202. The data storage unit 200 is realized by the storage unit 22. The operation reception unit 201 and the display control unit 202 are each realized by the control unit 21.

[0059] [Data storage section] The data storage unit 200 stores data necessary for the end-of-life planning support service. For example, the data storage unit 200 stores an end-of-life planning app, an EC app, and a browser.

[0060] [Operation reception section] The operation reception unit 201 receives various operations from the user. For example, the operation reception unit 201 receives operations for the end-of-life planning app, the EC app, and the browser. The operation reception unit 201 transmits data indicating the content of the user's operation to the server 10.

[0061] [Display control section] The display control unit 202 displays various screens on the display unit 25. For example, the display control unit 202 displays each of a menu screen SC1, an EC screen SC2, and an end-of-life planning support screen SC3 on the display unit 25. The display control unit 202 communicates with the server 10 or another computer, receives data necessary for displaying these screens, and displays these screens on the display unit 25.

[0062] [4. Processing performed by the end-of-life support system] Fig. 7 is a diagram showing an example of processing executed in the end-of-life planning support system 1. The processing of Fig. 7 is executed by the control units 11 and 21 executing programs stored in the storage units 12 and 22, respectively. It is assumed that the characteristics of the user have been estimated in advance, and that user characteristic information has been stored in advance in the user database DB.

[0063] 7, when a user selects the end-of-life planning app, the user terminal 20 launches the end-of-life planning app (S1). The user terminal 20 executes a login process with the server 10 to allow the user to log in to the end-of-life planning support service (S2). The server 10 acquires user characteristic information associated with the user ID of the logged-in user based on the user database DB (S3).

[0064] The server 10 executes processing for providing end-of-life planning support based on the user characteristic information and end-of-life planning support data with the user terminal 20 (S4), and this processing ends. In S4, the server 10 determines the order of buttons B31 associated with the characteristics indicated by the user characteristic information based on the end-of-life planning support data, and generates data (e.g., HTML data) for an end-of-life planning support screen SC3 based on the determined order and transmits it to the user terminal 20. Upon receiving the data, the user terminal 20 displays the end-of-life planning support screen SC3 on the display unit 25.

[0065] [5. Summary of embodiments] The end-of-life planning support system 1 of this embodiment acquires user characteristic information according to the user's usage of EC services. The end-of-life planning support system 1 provides end-of-life planning support based on the user characteristic information. This allows the end-of-life planning support system 1 to provide end-of-life planning support according to the user's characteristics, thereby improving user convenience. For example, even if the user's characteristics cannot be determined solely from the usage status of the end-of-life planning support service, if the user's characteristics can be estimated based on the user's usage status of the EC services they normally use, the end-of-life planning support system 1 can provide appropriate end-of-life planning support according to the user's characteristics. Even if the user does not know where to start with end-of-life planning, the end-of-life planning support provided by the end-of-life planning support system 1 allows the user to efficiently proceed with end-of-life planning.

[0066] [6. Modifications] The present disclosure is not limited to the above-described embodiments, and may be modified as appropriate without departing from the spirit of the present disclosure.

[0067] 8 is a diagram showing an example of functions realized in the modified example. For example, in the modified example, the server 10 includes a first usage determination unit 103, a second usage determination unit 104, and a user safety information acquisition unit 105. Each of the first usage determination unit 103, the second usage determination unit 104, and the user safety information acquisition unit 105 is realized by the control unit 11.

[0068] [6-1. Variation 1] For example, in the embodiment, an example is given of a case where user characteristic information is acquired according to the usage status of one web service such as an EC service, but the user characteristic information acquisition unit 101 may acquire user characteristic information according to the usage status of each of multiple web services. In Modification 1, an example is given of a case where an EC service and a payment service correspond to multiple web services. The number of multiple web services may be any number. The number of multiple web services is not limited to two. The number of multiple web services may be three or more.

[0069] The EC service of Variation 1 is the same as that of the embodiment. The payment service is a service that provides electronic payment (cashless payment) to the user. The payment service may be a known service. For example, the user uses the payment service from a payment app installed on the user terminal 20. The payment app is an application for the payment service. The user uses the payment service by displaying a code such as a two-dimensional code or a barcode on the payment app and having the code read by a terminal of a member store of the payment service. The user can use any payment method from among multiple payment methods such as credit cards, electronic money, and bank accounts.

[0070] The payment type in the payment service may be a known type, such as a type in which the user terminal 20 reads a code displayed on a terminal of the affiliated store, a type in which the user terminal 20 reads a code posted at the affiliated store, a type in which the payment is completed by operating the user terminal 20 alone, a type in which the IC chip in the user terminal 20 is read by the terminal of the affiliated store, a type in which an IC card is used instead of the user terminal 20, a type in which a card other than an IC card is used, or another type.

[0071] In Modification 1, an example is taken of a case where server 10 estimates user characteristics. Server 10 acquires usage status data indicating the usage status of a web service by a user from each of a plurality of web services. User characteristic information acquisition unit 101 of Modification 1 acquires user characteristic information by estimating the user's characteristics based on the usage status data of each of the plurality of web services.

[0072] For example, the server 10 acquires first usage data indicating the user's usage of the EC service from the EC service system. The first usage data is the same as the usage data described in the embodiment. The server 10 acquires second usage data indicating the user's usage of the payment service from the payment service system. The end-of-life planning support system 1 is linked to multiple services including the EC service and the payment service, and is capable of acquiring the first usage data and the second usage data.

[0073] In Variation 1, the items included in the second usage data are assumed to be the same as the items included in the first usage data. For example, the first usage data may include two items: the payment method used by the user in the EC service and the products purchased by the user in the EC service. In this case, the second usage data may include two items: the payment method used by the user in the payment service and the products purchased by the user in the payment service.

[0074] For example, the user characteristic information acquisition unit 101 acquires comprehensive usage data indicating the comprehensive usage of multiple services including e-commerce services and payment services based on the first usage data and the second usage data. The user characteristic information acquisition unit 101 calculates the total number of times users have used each payment method for each payment method based on the payment method indicated by the first usage data and the payment method indicated by the second usage data. The user characteristic information acquisition unit 101 calculates the total number of times users have purchased each product based on the product indicated by the first usage data and the product indicated by the second usage data. The user characteristic information acquisition unit 101 acquires comprehensive usage data indicating these total numbers of times. The total number of times may be calculated for each type (category) of product.

[0075] For example, the user characteristic information acquisition unit 101 acquires comprehensive usage data for various users in the same manner as described above. Based on the comprehensive usage data of each of the multiple users, the user characteristic information acquisition unit 101 performs clustering so that users with similar comprehensive usage data belong to the same cluster. An example of a clustering method is as described in the embodiment. When the comprehensive usage data includes multiple items, clustering may be performed for each item, or clustering may be performed by comprehensively considering the multiple items. Based on the results of the clustering, the user characteristic information acquisition unit 101 identifies which users belong to which cluster and generates user characteristic information.

[0076] For example, the user characteristic information acquisition unit 101 assigns a card characteristic to a user who belongs to a cluster indicating that the user tends to use a credit card for each of the EC service and the payment service. The user characteristic information acquisition unit 101 assigns a bank characteristic to a user who belongs to a cluster indicating that the user tends to use a bank account for each of the EC service and the payment service. The user characteristic information acquisition unit 101 assigns a home appliance characteristic to a user who belongs to a cluster indicating that the user tends to purchase home appliances. The user characteristic information acquisition unit 101 assigns a luxury item characteristic to a user who belongs to a cluster indicating that the user tends to purchase luxury items. The user characteristic information acquisition unit 101 acquires user characteristic information indicating the characteristics assigned to the user.

[0077] Note that, similar to the other systems described in the embodiments, the user characteristic information acquisition unit 101 may estimate user characteristics using methods other than clustering. For example, the user characteristic information acquisition unit 101 may acquire user characteristic information of a user based on a learning model that has learned the relationship between comprehensive usage data of a training user and the user characteristic information of the training user. The user characteristic information acquisition unit 101 inputs the comprehensive usage data of a user to be estimated into the trained learning model. The learning model calculates an embedded representation (e.g., a feature vector) of the comprehensive usage data input thereto based on parameters adjusted by learning, and outputs user characteristic information corresponding to the embedded representation. The user characteristic information acquisition unit 101 acquires the user characteristic information output from the learning model.

[0078] Also, similar to the embodiment, a system other than the end-of-life planning support system 1 may estimate user characteristics by aggregating usage status data indicating usage status of each of a plurality of web services from the web services. The other system may estimate user characteristics in the same manner as the user characteristic information acquisition unit 101 of the first modified example. In this case, the user characteristic information acquisition unit 101 acquires user characteristic information from the other system.

[0079] The end-of-life planning support unit 102 of the first modification provides end-of-life planning support based on user characteristic information corresponding to the usage status of each of the plurality of web services. Although the user characteristic information differs from the embodiment in that it indicates characteristics corresponding to the usage status of each of the plurality of web services, the process of providing end-of-life planning support based on the user characteristic information may be the same as the embodiment. For example, the end-of-life planning support unit 102 acquires end-of-life planning support information associated with the user characteristic information based on the user characteristic information and the end-of-life planning support data DT, and provides end-of-life planning support based on the end-of-life planning support information.

[0080] The end-of-life planning support system 1 of Variation 1 acquires user characteristic information according to the usage status of each of the multiple web services. The end-of-life planning support system 1 provides end-of-life planning support based on the user characteristic information according to the usage status of each of the multiple web services. As a result, the end-of-life planning support system 1 provides end-of-life planning support based on highly accurate user characteristic information that comprehensively takes into account the usage status of each of the multiple web services, thereby enabling more appropriate end-of-life planning support to be provided.

[0081] [6-2. Variation 2] For example, an end-of-life planning support service may support the surviving family members in completing procedures after the death of a user. In this case, the end-of-life planning support service needs to somehow detect whether the user has passed away. If the surviving family members notify the end-of-life planning support service that the user has passed away, the end-of-life planning support service can detect that the user has passed away. However, the surviving family members do not always notify the service.

[0082] In this regard, if a user logs in to the end-of-life planning support service, it is considered that the end-of-life planning support service can infer that the user is alive. Therefore, the server 10 may infer whether the user is alive or not based on whether the user has logged in to the end-of-life planning support service. For example, the server 10 determines whether the elapsed time since the user last logged in is equal to or greater than a threshold. If the server 10 determines that the elapsed time is less than the threshold, it determines that the user is alive. In this case, the notification described below is not sent.

[0083] For example, when the server 10 determines that the elapsed time is equal to or greater than a threshold, it inquires of the user to confirm whether the user is alive. The inquiry may be made by any means. For example, the notification may be made by email, push notification, banner notification, SMS, home appliance, or other means. The notification includes a link that accepts an operation from the user. The user operates the user terminal 20 to select the link in the notification and respond to the notification. The server 10 determines whether or not a response from the user has been received from the user terminal 20.

[0084] For example, if the server 10 determines that it has received a response from the user terminal 20, it determines that the user is alive. If the server 10 determines that it has not received a response from the user terminal 20, it waits a certain period of time and then repeatedly sends the above notification. The server 10 may determine that the user is not alive if the user does not respond to a predetermined number of notifications or if the user does not respond to a notification even after a predetermined time has passed since the last login. However, in this case, it may be that the user is alive but just happened not to have logged in to the end-of-life planning support service and missed the notification.

[0085] On the other hand, even if a user is not logged in to the end-of-life planning support service, the user may be logged in to a web service such as an e-commerce service. In this case, the user's survival can be estimated based on whether the user has used a web service linked to the end-of-life planning support service. Therefore, in Variation 2, an example is given in which the user's survival can be estimated based on whether the user has used a web service linked to the end-of-life planning support service.

[0086] The end-of-life planning support system 1 of the second modification includes a first usage determination unit 103. The first usage determination unit 103 determines whether or not the user has used a web service (a web service whose usage status is referenced when the user's characteristics are estimated) or another web service (a web service other than the web service whose usage status is referenced when the user's characteristics are estimated). The web service or another web service can be referred to as a web service other than the end-of-life planning support service.

[0087] For example, the server 10 acquires usage data indicating whether or not a web service or another web service has been used by a user from the web service or another web service system. When a user uses its service (e.g., when a user logs in), the web service or another web service system generates usage data with a value indicating that the user has used the service. When a user does not use its service (e.g., when a predetermined time has passed since the user last logged in), the web service or another web service system generates usage data with a value indicating that the user has not used the service.

[0088] For example, the first usage determination unit 103 determines whether the web service or another web service has been used by the user based on usage data acquired from the system of the web service or another web service. The first usage determination unit 103 may determine whether the web service or another web service has been used by the user based on the value indicated by the usage data.

[0089] The end-of-life planning support unit 102 of the second modification provides end-of-life planning support further based on the determination result of the first usage determination unit 103. For example, the end-of-life planning support unit 102 may determine whether or not to execute a predetermined process related to end-of-life planning support based on the determination result of the first usage determination unit 103. The predetermined process may be a process that is executed when it is determined that the web service or another web service has been used by the user, or may be a process that is executed when it is not determined that the web service or another web service has been used by the user.

[0090] The predetermined process may be any process related to end-of-life planning support. In Modification 2, an example is given in which the predetermined process corresponds to notification to the user or family. For example, if the end-of-life planning support unit 102 determines that the user has used a web service or other web services, the user is presumed to be alive and therefore does not issue a notification. If the end-of-life planning support unit 102 does not determine that the user has used a web service or other web services, the user may not be alive and therefore issues a notification.

[0091] The notification may include a message addressed to the user or a message addressed to the bereaved family. The message addressed to the user may be a message encouraging the user to log in to the end-of-life planning support service or to contact a person in charge of the end-of-life planning support service. The message addressed to the bereaved family may include content to confirm the user's safety, or may include content encouraging the user to take action in accordance with the end-of-life planning content information registered with the end-of-life planning support service. Data for notification (for example, a template message) is assumed to be stored in data storage unit 100.

[0092] Furthermore, the predetermined process is not limited to notifying the user or family. The predetermined process may be any process that has been determined in advance. For example, the predetermined process may be a notification to a person such as a lawyer, a notification to a person in charge of the end-of-life support service, a process of organizing digital belongings (for example, a process of deleting or freezing an SNS account), a process of outputting an end-of-life note that the user registered with the end-of-life support service, or other processes.

[0093] The end-of-life planning support system 1 of variant 2 determines whether the user has used the web service or other web services. The end-of-life planning support system 1 provides end-of-life planning support based on the results of the determination. This allows the end-of-life planning support system 1 to provide end-of-life planning support in cooperation with the web service or other web services, thereby further improving user convenience. For example, the end-of-life planning support system 1 can provide more flexible end-of-life planning support by presuming that the user is alive if the user has used the web service or other web services, and presuming that the user may not be alive if the user has not used the web service or other web services.

[0094] [6-3. Variation 3] For example, as explained somewhat in Modification 2, the server 10 may determine whether or not the end-of-life planning support service has been used by the user, and may provide end-of-life planning support in accordance with the results of the determination. The end-of-life planning support system 1 of Modification 3 includes a second usage determination unit 104. The second usage determination unit 104 determines whether or not the end-of-life planning support service related to end-of-life planning support has been used by the user. The processing of the second usage determination unit 104 may be similar to the processing of the server 10 explained in Modification 2.

[0095] For example, the second usage determination unit 104 determines whether the elapsed time since the user most recently logged in to the end-of-life planning support service is equal to or greater than a threshold. If the second usage determination unit 104 determines that the elapsed time is equal to or greater than the threshold, it does not determine that the user has used the end-of-life planning support service, and if the second usage determination unit 104 determines that the elapsed time is less than the threshold, it determines that the user has used the end-of-life planning support service. The second usage determination unit 104 may determine whether the user has used the end-of-life planning support service by determining whether access to the end-of-life planning support service has been received from the user terminal 20. If the second usage determination unit 104 does not determine that access to the end-of-life planning support service has been received from the user terminal 20, it may determine that the user has used the end-of-life planning support service, but if it determines that access to the end-of-life planning support service has been received from the user terminal 20, it may determine that the user has used the end-of-life planning support service.

[0096] The end-of-life planning support unit 102 of the third modification provides end-of-life planning support further based on the determination result of the second usage determination unit 104. For example, the end-of-life planning support unit 102 may determine whether or not to execute a predetermined process related to end-of-life planning support based on the determination result of the second usage determination unit 104. The predetermined process may be a process that is executed when it is determined that the end-of-life planning support service has been used by the user, or may be a process that is executed when it is not determined that the end-of-life planning support service has been used by the user.

[0097] The predetermined processing may be processing related to end-of-life planning support. In variant example 3, a case where notification to a user or a family member corresponds to the predetermined processing is taken as an example. For example, if it is determined that the user has used the end-of-life planning support service, the end-of-life planning support unit 102 does not issue a notification because it is assumed that the user is still alive. If it is not determined that the user has used the end-of-life planning support service, the end-of-life planning support unit 102 issues a notification because it is possible that the user is no longer alive.

[0098] The predetermined process is not limited to a notification to the user or family. The predetermined process may be any process that has been determined in advance. For example, the predetermined process may be a notification to a person such as a lawyer, a notification to a person in charge of the end-of-life support service, a process of organizing digital belongings (for example, a process of deleting or freezing an SNS account), a process of outputting an end-of-life note that the user registered with the end-of-life support service, or other processes.

[0099] The end-of-life planning support system 1 of variant 3 determines whether or not the end-of-life planning support service has been used by the user. The end-of-life planning support system 1 provides end-of-life planning support based on the results of this determination. This allows the end-of-life planning support system 1 to provide flexible end-of-life planning support in accordance with the determination of whether or not the end-of-life planning support service has been used, thereby further improving user convenience. For example, the end-of-life planning support system 1 can provide more flexible end-of-life planning support by presuming that the user is alive if the end-of-life planning support web service has been used, and by presuming that the user may not be alive if the end-of-life planning support service has not been used by the user.

[0100] [6-4. Variation 4] For example, as explained somewhat in Modifications 2 and 3, end-of-life planning support may be provided depending on the user's safety. The end-of-life planning support system 1 of Modification 4 includes a user safety information acquisition unit 105. The user safety information acquisition unit 105 acquires user safety information regarding the user's safety. The user safety information indicates either a value indicating that the user is alive, or a value indicating the possibility that the user is not alive. The user safety information acquisition unit 105 acquires the user safety information by estimating the user's safety based on a predetermined method.

[0101] The user's safety may be estimated by a predetermined method. For example, as in Modification 2, the user's safety may be estimated based on the result of determining whether or not a web service or another web service has been used, or as in Modification 3, the user's safety may be estimated based on the result of determining whether or not an end-of-life planning support service has been used. The user safety information acquisition unit 105 may acquire user safety information using a monitoring function adopted in a known security service. For example, the monitoring function may be a method that uses a camera or sensor of the user terminal 20 and a camera or sensor installed in the user's home.

[0102] The end-of-life planning support unit 102 of Variation 4 provides end-of-life planning support by organizing the user's digital remains based further on the user safety information. The process of organizing the digital remains may be a process of displaying an end-of-life planning support screen SC3 that summarizes how to organize the digital remains, or may be a process of notifying a person managing the digital remains (for example, the operator of the end-of-life planning support service, the user's family, or a lawyer), or may be a process of deleting or freezing the digital remains. If the user safety information indicates that the user is still alive, the end-of-life planning support unit 102 does not perform the process of organizing the digital remains, but if the user safety information indicates that the user may not be still alive, it performs the process of organizing the digital remains.

[0103] The end-of-life planning support system 1 of Variation 4 provides end-of-life planning support by organizing the user's digital belongings based on the user's safety information. This allows the end-of-life planning support system 1 to provide flexible end-of-life planning support in accordance with the user's safety information. For example, if the user safety information indicates that the user may no longer be alive, the end-of-life planning support system 1 can execute a process to organize the digital belongings, thereby streamlining the organization of the digital belongings.

[0104] [6-5. Variation 5] For example, the end-of-life planning support unit 102 may provide end-of-life planning support to the user by proposing to the user an integrated service that is integrated with an end-of-life planning support service related to end-of-life planning support. The integrated service is a web service other than the end-of-life planning support service. The integrated service may be the same as the web service whose usage status is referenced to estimate the user's characteristics, or it may be a web service different from the web service. The proposal of the integrated service involves displaying information about the integrated service's system on the end-of-life planning support screen SC3. For example, a character string or image indicating the content of the integrated service, a link to the integrated service's system, or other information may be displayed on the end-of-life planning support screen SC3. These images, links, or other information are assumed to be stored in the data storage unit 100. The end-of-life planning support unit 102 proposes the integrated service based on the data.

[0105] FIG. 9 is a diagram showing an example of the end-of-life planning support screen SC3 in Modification 5. Modification 5 takes as an example a case where a travel booking service is provided as an associated service. Furthermore, take as an example a case where a travel lover characteristic indicating a love of travel is estimated as a user characteristic. For example, when the characteristic is estimated from the usage status of an EC service, the user characteristic information acquisition unit 101 acquires user characteristic information indicating a love of travel characteristic when the user tends to purchase travel goods.

[0106] For example, if the user characteristic information does not indicate a travel lover characteristic, the end-of-life planning support unit 102 does not suggest an integrated service to the user, and if the user characteristic information indicates a travel lover characteristic, the end-of-life planning support unit 102 suggests an integrated service to the user. In the example of Figure 9, the end-of-life planning support unit 102 suggests a travel reservation service to the user by displaying a button B32 including a link to a travel reservation service, which is an example of an integrated service.

[0107] The linked service is not limited to a travel reservation service. The linked service may be any web service related to end-of-life planning support and linked to the end-of-life planning support service. For example, the linked service may be a credit card service, a financial service, an insurance service, a social networking service, or another web service. The characteristics for which the linked service should be proposed to the user may be predetermined. The end-of-life planning support data DT defines which characteristics should lead to the linked service being proposed. The user characteristic information acquisition unit 101 may not propose the linked service to the user if the user characteristic information does not indicate a predetermined characteristic based on the end-of-life planning support data DT, and may propose the linked service to the user if the user characteristic information indicates a predetermined characteristic.

[0108] In addition, there may be multiple linked services. In this case, the end-of-life planning support data DT is associated with user characteristic information and end-of-life planning support information indicating a linked service to be proposed to the user from among the multiple linked services. Based on the end-of-life planning support data DT, the end-of-life planning support unit 102 proposes to the user the linked service indicated by the end-of-life planning support information associated with the user characteristic information acquired from the user characteristic information.

[0109] The end-of-life planning support system 1 of the fifth modification example provides support for end-of-life planning by proposing linked services to the user. Because the user can learn about appropriate linked services that correspond to their own characteristics, the end-of-life planning support system 1 can further enhance user convenience. For example, a user who likes to travel can learn about travel reservation services to use as part of end-of-life planning, allowing them to plan their end-of-life planning.

[0110] [6-6. Variation 6] For example, the end-of-life planning support unit 102 may obtain end-of-life planning content information regarding end-of-life planning carried out by other users who have characteristics corresponding to the user based on the user characteristic information, and provide end-of-life planning support based on the end-of-life planning content information. The characteristics corresponding to a user are the same characteristics as the user. If similar characteristics are defined in advance, characteristics similar to the user's characteristics may correspond to the characteristics corresponding to the user. The end-of-life planning support unit 102 may identify other users who have characteristics similar to the user's characteristics based on similar characteristic data in which similar characteristics are defined. Other users also use the end-of-life planning support service. Other users have registered their own end-of-life planning plans with the end-of-life planning support service.

[0111] For example, another user launches an end-of-life planning app installed on their own user terminal 20 and inputs their own end-of-life planning plan. The server 10 associates the end-of-life planning content information indicating the end-of-life planning plan input by the other user with the user ID of the other user and stores it in the user database DB. The user characteristic information of the other user is assumed to have been acquired by the user characteristic information acquisition unit 101 and stored in the user database DB, as in the embodiment.

[0112] For example, the end-of-life planning support unit 102 acquires end-of-life planning content information of other users who store the same user characteristic information as the user's user characteristic information from the user database DB. If there are multiple other users who store the same user characteristic information as the user's user characteristic information, the end-of-life planning support unit 102 may acquire end-of-life planning content information of all of the multiple users, or may acquire end-of-life planning content information of some of the multiple users.

[0113] FIG. 10 is a diagram showing an example of the end-of-life planning support screen SC3 of variant example 6. As shown in FIG. 10, the end-of-life planning support unit 102 displays all or part of the content indicated by the end-of-life planning content information of other users on the end-of-life planning support screen SC3. In the example of FIG. 10, the process of end-of-life planning actually carried out by other users is displayed on the end-of-life planning support screen SC3 as anonymous information. Since the end-of-life planning content information may include information (e.g., personal information) that other users do not want to make public, the end-of-life planning support unit 102 may display all or part of the content of the end-of-life planning content information from which that information has been excluded on the end-of-life planning support screen SC3. The exclusion of that information may be performed by an administrator of the end-of-life planning support service, or may be performed using a model such as a large-scale language model.

[0114] The end-of-life planning support system 1 of the sixth modification acquires end-of-life planning content information about end-of-life planning carried out by other users who have characteristics corresponding to the user based on user characteristic information, and provides end-of-life planning support based on the end-of-life planning content information. This allows the user to carry out their own end-of-life planning by referring to the content of end-of-life planning carried out by other users who have characteristics corresponding to the user, so the end-of-life planning support system 1 can further increase convenience for the user.

[0115] [6-7. Variation 7] For example, the end-of-life planning support unit 102 may provide end-of-life planning support further based on a learning model that learns the relationship between training user characteristic information related to the characteristics of a training user who is different from the user and training end-of-life planning support information related to end-of-life planning support for the training user. The learning model of Variation 7 may utilize any machine learning method, similar to the learning model of the embodiment. For example, the learning model of Variation 7 may be a neural network, a support vector machine, a large-scale language model, or another model. In Variation 7, the learning model corresponds to the end-of-life planning support data DT described in the embodiment.

[0116] The training user may be another user who has actually used the end-of-life planning support service, or may be a fictitious user envisioned by the administrator of the end-of-life planning support service. The training user characteristic information differs from the user characteristic information described in the embodiment in that it indicates the characteristics of the training user, but is similar to the user characteristic information described in the embodiment in other respects. The training end-of-life planning support information is content of end-of-life planning support appropriate for the training user. The training end-of-life planning support information differs from the end-of-life planning support information described in the embodiment in that it is intended for the training user, but is similar to the end-of-life planning support information described in the embodiment in other respects.

[0117] For example, the data storage unit 100 stores training data including training user characteristic information and training end-of-life support information. The data storage unit 100 may store a plurality of training data. The training user characteristic information included in the training data is an input portion that is input to the learning model during learning. The input portion may include other information. The training end-of-life support information included in the training data is an output portion that should be output from the learning model during learning (an output portion that is the correct answer during learning).

[0118] For example, the server 10 executes learning of the learning model so that when training user characteristic information, which is the input part of the training data, is input, training subject and support information, which is the output part of the training data, is output. The algorithm for learning the learning model may be an algorithm adopted in known machine learning. The loss function, etc. used in learning may also be known. Learning may be performed on a computer other than the server 10. Learning may also correspond to fine-tuning, in which a trained learning model is fine-tuned using training data.

[0119] For example, the data storage unit 100 stores a trained learning model. The end-of-life planning support unit 102 inputs the user's user characteristic information to the learning model. The learning model calculates an embedded representation (e.g., a feature vector) of the user characteristic information based on parameters adjusted by learning. The learning model outputs end-of-life planning support information corresponding to the calculated embedded representation. The end-of-life planning support unit 102 provides end-of-life planning support based on the end-of-life planning support information. Although the present embodiment differs from the embodiment in that the end-of-life planning support information is acquired by the learning model, the content indicated by the end-of-life planning support information and the end-of-life planning support processing based on the end-of-life planning support information may be the same as the embodiment.

[0120] The end-of-life planning support system 1 of the seventh modification provides end-of-life planning support based on a learning model that has learned the relationship between the training user characteristic information and the training end-of-life planning support information. This allows the end-of-life planning support system 1 to provide highly accurate end-of-life planning support using the learning model, thereby further improving user convenience.

[0121] [6-8. Variation 8] For example, in variant 7, the training end-of-life planning support information may indicate an end-of-life planning plan created by the training user. The end-of-life planning plan is at least one specific plan for end-of-life planning. The training user operates their own user terminal 20 to input their own end-of-life planning plan. The server 10 acquires the training end-of-life planning support information indicating the end-of-life planning plan input by the training user. The process for having the learning model learn the training end-of-life planning support information may be the same as variant 8. The input portion of the training data may include not only training user characteristic information but also other information such as the training user's user registration information.

[0122] The end-of-life planning support unit 102 of Variation 8 provides end-of-life planning support by having a learning model generate an end-of-life planning plan appropriate for the user. The end-of-life planning support unit 102 inputs the user's user characteristic information to the learning model. The learning model calculates an embedded representation (e.g., a feature vector) of the user characteristic information based on parameters adjusted by learning. The learning model outputs end-of-life planning support information indicating an end-of-life planning plan corresponding to the calculated embedded representation. If the input portion of the training data includes other information such as the user registration information of the training user, the end-of-life planning support unit 102 also inputs the other information such as the user's user registration information to the learning model. The learning model calculates an embedded representation that takes the other information into consideration and outputs end-of-life planning support information.

[0123] For example, the end-of-life planning support unit 102 provides end-of-life planning support based on the end-of-life planning plan indicated by the end-of-life planning support information. For example, the end-of-life planning support unit 102 provides end-of-life planning support by displaying the end-of-life planning plan indicated by the end-of-life planning support information on the end-of-life planning support screen SC3. Although the end-of-life planning support information output by the learning model differs from Variation 7 in indicating the end-of-life planning plan, the content indicated by the end-of-life planning support information and the end-of-life planning support processing based on the end-of-life planning support information may be the same as Variation 7.

[0124] The end-of-life planning support system 1 of the eighth modification provides end-of-life planning support by having the learning model generate an end-of-life planning plan appropriate for the user. This allows the end-of-life planning support system 1 to generate an appropriate end-of-life planning plan using the learning model, thereby further improving user convenience.

[0125] [6-9. Variation 9] For example, in variant 7, the training end-of-life planning support information may indicate the training user's autobiography. An autobiography is a document in which at least a part of one's life is described in a narrative style. The training user operates his or her user terminal 20 to input his or her autobiography. The server 10 acquires the training end-of-life planning support information indicating the autobiography input by the training user. If the training user is a fictitious user, the training end-of-life planning support information may indicate a fictitious autobiography created by an administrator of the end-of-life planning support service. The process of having the learning model learn the training end-of-life planning support information may be the same as variant 7. The input portion of the training data may include not only training user characteristic information but also other information such as the training user's user registration information.

[0126] The end-of-life planning support unit 102 of Variation 9 provides end-of-life planning support by generating a user's autobiography in a learning model. The end-of-life planning support unit 102 inputs the user's user characteristic information to the learning model. The learning model calculates an embedded representation (e.g., a feature vector) of the user characteristic information based on parameters adjusted by learning. The learning model outputs end-of-life planning support information indicating the autobiography corresponding to the calculated embedded representation. If the input portion of the training data includes other information such as the training user's user registration information, the end-of-life planning support unit 102 also inputs the other information such as the user's user registration information into the learning model. The learning model calculates an embedded representation that takes the other information into consideration and outputs end-of-life planning support information.

[0127] For example, the end-of-life planning support unit 102 provides end-of-life planning support based on the autobiography indicated by the end-of-life planning support information. For example, the end-of-life planning support unit 102 provides end-of-life planning support by displaying the autobiography indicated by the end-of-life planning support information on the end-of-life planning support screen SC3. Although this differs from Variation 7 in that the end-of-life planning support information output by the learning model indicates an autobiography, the content indicated by the end-of-life planning support information and the end-of-life planning support processing based on the end-of-life planning support information may be the same as Variation 7.

[0128] The end-of-life planning support system 1 of the modification 9 supports end-of-life planning by generating the user's autobiography in a learning model. This allows the end-of-life planning support system 1 to generate an appropriate autobiography using the learning model, thereby further improving user convenience.

[0129] [6-10. Variation 10] For example, the end-of-life planning support unit 102 may provide end-of-life planning support by proposing an order in which the user should decide on each of a plurality of items prepared for end-of-life planning. The end-of-life planning support data DT of Modification 10 defines a relationship between user characteristic information and end-of-life planning support information that indicates an appropriate order for the plurality of items. The end-of-life planning support unit 102 acquires end-of-life planning support information associated with the user characteristic information of the user based on the end-of-life planning support data DT, and provides end-of-life planning support based on the order indicated by the end-of-life planning support information.

[0130] For example, the end-of-life planning support unit 102 may provide end-of-life planning support by displaying the order indicated by the acquired end-of-life planning support information on the end-of-life planning support screen SC3. The end-of-life planning support unit 102 may provide end-of-life planning support by displaying the end-of-life planning support screen SC3 on the user terminal 20, on which input forms for accepting input for individual items are arranged in the order indicated by the acquired end-of-life planning support information. If information for each item is entered on a separate page, the end-of-life planning support unit 102 may provide end-of-life planning support by displaying the end-of-life planning support screen SC3 on the user terminal 20, on which pages for accepting input for individual items are displayed one after another in the order indicated by the acquired end-of-life planning support information.

[0131] The end-of-life planning support system 1 of the tenth modification supports end-of-life planning by proposing the order in which the user should decide on each of the multiple items prepared for end-of-life planning. This allows the end-of-life planning support system 1 to carry out end-of-life planning in an appropriate order according to the characteristics of the user, thereby further improving convenience for the user.

[0132] [6-11. Variation 11] For example, in Modification 10, the end-of-life planning support unit 102 may propose an order to be determined by the user based on a learning model that has learned the relationship between training user characteristic information relating to the characteristics of a training user who is different from the user and training order information relating to the order of each of a plurality of items determined by the training user. The learning model of Modification 11 may utilize any machine learning method, similar to the learning models of the embodiment and Modifications 7 to 9. For example, the learning model of Modification 11 may be a neural network, a support vector machine, a large-scale language model, or another model. In Modification 11, the learning model corresponds to the end-of-life planning support data DT described in the embodiment.

[0133] The training order information is information that indicates an appropriate order for the training user. For example, the data storage unit 100 stores training data including training user characteristic information and training order information. The data storage unit 100 may store a plurality of training data. The input portion of the training data may be the same as in Modifications 7 to 9. Modifications 7 to 9 differ from Modifications 7 to 9 in that the output portion of the training data is training order information, but may be the same as in Modifications 7 to 9 in other respects. The algorithm for learning the learning model may also be the algorithm adopted in known machine learning, as in Modifications 7 to 9.

[0134] For example, the data storage unit 100 stores a trained learning model. The end-of-life planning support unit 102 inputs the user's user characteristic information to the learning model. The learning model calculates an embedded representation (e.g., a feature vector) of the user characteristic information based on parameters adjusted by learning. The learning model outputs end-of-life planning support information indicating an order according to the calculated embedded representation. The end-of-life planning support unit 102 provides end-of-life planning support based on the end-of-life planning support information. Although this embodiment differs from the embodiment in that the end-of-life planning support information is obtained by the learning model, the method of proposing the order may be the same as in variant example 10.

[0135] The end-of-life planning support system 1 of the modification 11 proposes the order that the user should decide based on the learning model that has learned the relationship between the training user characteristic information and the training order information. This allows the end-of-life planning support system 1 to provide highly accurate end-of-life planning support using the learning model, thereby further improving user convenience.

[0136] [6-12. Variation 12] For example, the end-of-life planning support unit 102 may provide end-of-life planning support by matching a user with a target of use that the user will use in end-of-life planning. The target of use may be a person such as a lawyer or financial planner, or an organization such as a card company or funeral company. The target of use may be a facility such as a funeral home or temple. The target of use may be a product or service. For example, a product or service necessary for end-of-life planning may correspond to the target of use. Matching involves identifying information about a target of use that is appropriate for the user and outputting that information. It is assumed that the information about the target of use is stored in the data storage unit 100.

[0137] In the end-of-life planning support data DT of variant example 11, a relationship is defined between user characteristic information and end-of-life planning support information indicating an appropriate target for use. For example, a relationship indicating which lawyer is appropriate for which characteristic is defined in the end-of-life planning support data DT. A relationship indicating which financial planner is appropriate for which characteristic is defined in the end-of-life planning support data DT. A relationship indicating which facility is appropriate for which characteristic may be defined in the end-of-life planning support data DT. A relationship indicating which product or service is appropriate for which characteristic may be defined in the end-of-life planning support data DT. If the end-of-life planning support data DT is a machine learning model, the relationship indicating which target for use is appropriate for which characteristic is learned in advance.

[0138] For example, the end-of-life planning support unit 102 acquires end-of-life planning support information associated with the user's user characteristic information based on the end-of-life planning support data DT, and provides end-of-life planning support based on the intended use indicated by the end-of-life planning support information. The end-of-life planning support unit 102 provides end-of-life planning support by displaying the intended use indicated by the acquired end-of-life planning support information on the end-of-life planning support screen SC3. For example, the end-of-life planning support unit 102 displays information about lawyers associated with the characteristics indicated by the user characteristic information in the end-of-life planning support data DT on the end-of-life planning support screen SC3. The end-of-life planning support unit 102 displays information about financial planners associated with the characteristics indicated by the user characteristic information in the end-of-life planning support data DT on the end-of-life planning support screen SC3.

[0139] For example, the end-of-life planning support unit 102 displays information about facilities associated with the characteristics indicated by the user characteristic information in the end-of-life planning support data DT on the end-of-life planning support screen SC3. The end-of-life planning support unit 102 displays information about products or services associated with the characteristics indicated by the user characteristic information in the end-of-life planning support data DT on the end-of-life planning support screen SC3. If the end-of-life planning support data DT is a learning model, the end-of-life planning support unit 102 inputs the user characteristic information into the learning model, identifies an appropriate target of use based on the output from the learning model, and displays information about the target of use on the end-of-life planning support screen SC3.

[0140] The end-of-life planning support system 1 of the modification 12 supports end-of-life planning by matching users with the target of use that the user will use in end-of-life planning. This allows the user to know the target of use that is appropriate for their own characteristics, so the end-of-life planning support system 1 can further improve the convenience for the user.

[0141] [6-13. Other variations] For example, the above modifications may be combined.

[0142] For example, the functions described as being realized by the server 10 may be realized by another computer such as the user terminal 20. The functions described as being realized by the server 10 may be shared among multiple computers.

[0143] [7. Notes] For example, the end-of-life support system can be configured as follows: (1) a user characteristic information acquisition unit that acquires user characteristic information relating to characteristics according to a user's usage of the web service; An end-of-life planning support unit that provides end-of-life planning support, which is an activity for approaching the end of life, based on the user characteristic information; A support system for end-of-life planning, including: (2) the user characteristic information acquisition unit acquires the user characteristic information according to a usage status of each of the plurality of web services; The end-of-life planning support unit performs the end-of-life planning support based on the user characteristic information according to the usage status of each of the plurality of web services. (1) The end-of-life support system described above. (3) The end-of-life planning support system further includes a first usage determination unit that determines whether the user has used the web service or another web service, The end-of-life planning support unit performs the end-of-life planning support further based on the determination result of the first usage determination unit, (1) or (2) described end-of-life support system. (4) The end-of-life planning support system further includes a second usage determination unit that determines whether the user has used an end-of-life planning support service related to the end-of-life planning support, The end-of-life planning support unit performs the end-of-life planning support further based on the determination result of the second usage determination unit, A support system for end-of-life planning according to any one of (1) to (3). (5) The end-of-life planning support system further includes a user safety information acquisition unit that acquires user safety information regarding the safety of the user, The end-of-life support unit performs the end-of-life support by organizing digital remains related to the user based on the user safety information. A support system for end-of-life planning according to any one of (1) to (4). (6) The end-of-life support unit provides the end-of-life support by proposing to the user a linked service that links with the end-of-life support service related to the end-of-life support. A support system for end-of-life planning according to any one of (1) to (5). (7) The end-of-life planning support unit acquires end-of-life planning content information regarding the end-of-life planning performed by other users having characteristics corresponding to the user based on the user characteristic information, and performs the end-of-life planning support based on the end-of-life planning content information. A support system for end-of-life planning described in any one of (1) to (6). (8) The end-of-life planning support unit performs the end-of-life planning support based on a learning model in which the relationship between training user characteristic information regarding the characteristics of a training user different from the user and training end-of-life planning support information regarding the end-of-life planning support for the training user is learned. A support system for end-of-life planning according to any one of (1) to (7). (9) The training end-of-life planning support information indicates an end-of-life planning plan created by the training user, The end-of-life planning support unit performs the end-of-life planning support by causing the learning model to generate an end-of-life planning plan appropriate for the user. (8) The end-of-life support system described in (8). (10) The training end-of-life support information indicates an autobiography of the training user, The end-of-life planning support unit performs the end-of-life planning support by generating the user's autobiography in the learning model. (8) or (9) described end-of-life support system. (11) The end-of-life planning support unit performs the end-of-life planning support by proposing an order in which the user should decide each of a plurality of items prepared for the end-of-life planning. A support system for end-of-life planning according to any one of (1) to (10). (12) The end-of-life planning support unit proposes an order to be decided by the user based on a learning model in which a relationship between training user characteristic information regarding characteristics of a training user different from the user and training order information regarding the order of each of the plurality of items decided by the training user has been learned. (11) The end-of-life support system described in (11). (13) The end-of-life planning support unit performs the end-of-life planning support by matching the user with a target to be used by the user in the end-of-life planning. A support system for end-of-life planning according to any one of (1) to (12). [Explanation of symbols]

[0144] 1 End-of-life planning support system, N network, 10 server, 11, 21 control unit, 12, 22 memory unit, 13, 23 communication unit, 20 user terminal, 24 operation unit, 25 display unit, DB user database, DT end-of-life planning support data, 100 data storage unit, 101 user characteristic information acquisition unit, 102 end-of-life planning support unit, 103 first usage determination unit, 104 second usage determination unit, 105 user safety information acquisition unit, 200 data storage unit, 201 operation reception unit, 202 display control unit, B30, B31, B32 buttons, I10, I11 icons, SC1 menu screen, SC2 EC screen, SC3 end-of-life planning support screen.

Claims

1. a user characteristic information acquisition unit that acquires user characteristic information relating to characteristics according to a user's usage of the web service; An end-of-life planning support unit that provides end-of-life planning support, which is an activity for approaching the end of life, based on the user characteristic information; A support system for end-of-life planning, including:

2. the user characteristic information acquisition unit acquires the user characteristic information according to a usage status of each of the plurality of web services; The end-of-life planning support unit performs the end-of-life planning support based on the user characteristic information according to the usage status of each of the plurality of web services. The end-of-life planning support system according to claim 1.

3. The end-of-life planning support system further includes a first usage determination unit that determines whether the web service or another web service has been used by the user, The end-of-life support unit performs the end-of-life support further based on the determination result of the first usage determination unit, The end-of-life support system according to claim 1 or 2.

4. The end-of-life planning support system further includes a second usage determination unit that determines whether the user has used an end-of-life planning support service related to the end-of-life planning support, The end-of-life support unit performs the end-of-life support further based on the determination result of the second usage determination unit, The end-of-life support system according to claim 1 or 2.

5. The end-of-life planning support system further includes a user safety information acquisition unit that acquires user safety information regarding the safety of the user, The end-of-life support unit performs the end-of-life support by organizing digital remains related to the user based on the user safety information. The end-of-life support system according to claim 1 or 2.

6. The end-of-life support unit provides the end-of-life support by proposing to the user a linked service that links with the end-of-life support service related to the end-of-life support. The end-of-life support system according to claim 1 or 2.

7. The end-of-life planning support unit acquires end-of-life planning content information regarding the end-of-life planning performed by other users having characteristics corresponding to the user based on the user characteristic information, and performs the end-of-life planning support based on the end-of-life planning content information. The end-of-life support system according to claim 1 or 2.

8. The end-of-life planning support unit performs the end-of-life planning support based on a learning model in which the relationship between training user characteristic information regarding the characteristics of a training user different from the user and training end-of-life planning support information regarding the end-of-life planning support for the training user is learned. The end-of-life support system according to claim 1 or 2.

9. The training end-of-life planning support information indicates an end-of-life planning plan created by the training user, The end-of-life planning support unit performs the end-of-life planning support by causing the learning model to generate an end-of-life planning plan appropriate for the user. The end-of-life planning support system according to claim 8.

10. The training end-of-life support information indicates an autobiography of the training user, The end-of-life planning support unit performs the end-of-life planning support by generating the user's autobiography in the learning model. The end-of-life planning support system according to claim 8.

11. The end-of-life planning support unit performs the end-of-life planning support by proposing an order in which the user should decide each of a plurality of items prepared for the end-of-life planning. The end-of-life support system according to claim 1 or 2.

12. The end-of-life planning support unit proposes an order to be decided by the user based on a learning model in which a relationship between training user characteristic information regarding characteristics of a training user different from the user and training order information regarding the order of each of the plurality of items decided by the training user has been learned. The end-of-life planning support system according to claim 11.

13. The end-of-life planning support unit performs the end-of-life planning support by matching the user with a target to be used by the user in the end-of-life planning. The end-of-life support system according to claim 1 or 2.

14. a user characteristic information acquisition step of acquiring user characteristic information relating to characteristics according to a usage situation of the web service by the user; An end-of-life planning support step of providing end-of-life planning support, which is an activity for approaching the end of life, based on the user characteristic information; End-of-life support methods, including:

15. a user characteristic information acquisition unit that acquires user characteristic information relating to characteristics according to a user's usage of the web service; An end-of-life planning support department that provides end-of-life planning support, which is an activity for approaching the end of life, based on the user characteristic information; A program that allows a computer to function as a

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