Life plan proposal apparatus, life plan proposal system, life plan proposal method, and computer program

Abstract

To propose a future plan of a user tailored to the current condition of the user without information on the future plan obtained from the user.SOLUTION: An acquisition unit acquires attribute information indicating a user and living condition information related to a living condition of the user. An expansion unit adds additional attribute information of the user by an information generation method using the acquired attribute information. An estimation unit estimates a life event that is likely to happen in the user's life and a time of the life event by using the attribute information including the added attribute information, and the living condition information of the user. An output unit outputs a life plan generated by using information of the estimated life event.SELECTED DRAWING: Figure 13

Description

Technical Field

[0001] The present disclosure relates to a life plan proposal device, a life plan proposal system, a life plan proposal method, and a computer program that propose a life plan.

Background Art

[0002] Patent Document 1 (International Publication No. 2023 / 112745) discloses a technique for generating a user's future plan. In the technique disclosed in Patent Document 1, the user's future plan information is generated based on the user's basic information and ideal future plan, and the user's future plan information is corrected according to the user's reaction to the viewed future plan information.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, it is not uncommon for future events predicted by a user when making a future plan to occur at a time different from the predicted time. For this reason, even if a user makes a future plan, it often happens that the user's future plan deviates from the current situation and becomes useless due to the time of the event predicted to occur deviating from the prediction.

[0005] The present disclosure was conceived to solve the above-described problems. That is, the main object of the present disclosure is to provide a technique for proposing a user's future plan that suits the user's current situation even without information regarding the user's future plan.

Means for Solving the Problems

[0006] To achieve the above object, in one aspect, the life plan proposal apparatus in the present disclosure an acquisition unit that acquires attribute information representing a user and life situation information regarding the user's life situation; an extension unit that adds further attribute information of the user by an information generation method using the acquired attribute information; an estimation unit that estimates a life event likely to occur to the user and the timing thereof using the attribute information of the user including the added attribute information and the life situation information; an output unit that outputs a life plan generated using the information of the estimated life event is provided.

[0007] Also, in one aspect, the life plan proposal system in the present disclosure acquisition means for acquiring attribute information representing a user and life situation information regarding the user's life situation; extension means for adding further attribute information of the user by an information generation method using the acquired attribute information; estimation means for estimating a life event likely to occur to the user and the timing thereof using the attribute information of the user including the added attribute information and the life situation information; output means for outputting a life plan generated using the information of the estimated life event is provided.

[0008] Furthermore, in one aspect, the life plan proposal method in the present disclosure by a computer, acquires attribute information representing a user and life situation information regarding the user's life situation, adds further attribute information of the user by an information generation method using the acquired attribute information, estimates a life event likely to occur to the user and the timing thereof using the attribute information of the user including the added attribute information and the life situation information, and outputs a life plan generated using the information of the estimated life event.

[0009] Furthermore, as one aspect of the computer program in the present disclosure, a process of acquiring attribute information representing a user and life situation information regarding the user's life situation, a process of adding additional attribute information of the user by an information generation method using the acquired attribute information, a process of estimating a likely life event and its timing for the user using the user's attribute information and life situation information including the added attribute information, and a process of outputting a life plan generated using the information on the estimated life event are executed by a computer.

Advantages of the Invention

[0010] According to the present disclosure, it is possible to propose a future plan for the user that suits the user's current situation even without information regarding the user's future plans.

Brief Description of the Drawings

[0011]

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[0012] Hereinafter, embodiments in the present disclosure will be described with reference to the drawings.

[0013] <First Embodiment> (Definition and Application Examples of Life Plan) For facilitating understanding of the first embodiment, the definition of a life plan will be explained. A life plan refers to the process of setting goals and dreams in an individual's life and formulating plans to achieve them. This process includes various aspects of life such as financial plans, career goals, family plans, retirement plans, etc. Goal setting is the specific dreams and wishes that an individual wants to achieve, and a plan means the step-by-step actions and methods to realize these goals. The time frame sets the period for achieving the goal, and resource management is related to securing and managing the necessary resources (money, time, skills, etc.).

[0014] In an example of a career plan, aiming to be promoted to a department manager by the age of 40, it includes specific action plans such as participating in training for skill improvement and enhancing performance. In a financial plan, setting a goal to purchase a house by the age of 35 and advancing the plan through monthly savings, investments, and selection of a housing loan. In a family plan, aiming to have two children and making preparations for the funds required for child-rearing, planning for parental leave, and saving for education expenses. In a retirement plan, with the goal of retiring at the age of 60 and enjoying a life of hobbies and travel afterwards, focusing on calculating retirement benefits, investing in hobbies, and health management.

[0015] Financial institutions utilize an individual's life plan to provide customized financial services and advice to customers. By understanding the customer's life plan, financial institutions can offer savings plans, investment strategies, loan proposals, and insurance product selections tailored to the customer's needs.

[0016] For example, for customers aiming for career advancement, educational loans and investment products for career improvement are proposed. Also, for customers planning to purchase a house, options for housing loans and savings plans for home purchase are provided. In the case of a family plan focused on children's education expenses, savings accounts for educational funds and educational insurance proposals are made.

[0017] (Device Configuration) The life plan proposal device of the first embodiment is a computer device that provides a life plan proposal service, generates and updates a life plan, and proposes a life plan suitable for the user's current situation. Also, the life plan proposal device of the first embodiment has a function of attempting to propose an updated version of the life plan suitable for the user's current situation even if update information is not provided by the user.

[0018] That is, the life plan proposal device (hereinafter also abbreviated as the proposal device) 1 of the first embodiment has a configuration as shown in FIG. 1, for example, and is connected to the terminal device 3. The terminal device 3 is an information device operated by a user who uses the life plan proposal service provided by the proposal device 1, for example, and has a communication function and a display control function. The communication function is a function of communicating information with other devices with a communication function via an information communication network such as the Internet. The display control function is a function of causing the display device 4 to display information by controlling the display operation of the display device 4. The type of the terminal device 3 is not limited as long as it is an information device having such a communication function and a display control function. Specific examples include smartphones, tablets, personal computers (PCs), and the like. When the terminal device 3 is a smartphone or a tablet, the display device 4 is integrated with the terminal device 3. However, when the terminal device 3 is a personal computer, the display device may be external. In the example of FIG. 1, there is one terminal device 3 connected to the proposal device 1. However, the number of terminal devices 3 connected to the proposal device 1 is not limited, and there may be a plurality of them. Even when a plurality of terminal devices 3 are connected to the proposal device 1, the proposal device 1 performs the same functions for each of the terminal devices 3. Therefore, the description of the case where a plurality of terminal devices 3 are connected is omitted here.

[0019] The terminal device 3 exchanges information with the proposal device 1 and cooperates with the proposal device 1 through an application program (app) or a browser (software for browsing information on the Internet) for providing the function of cooperating with the proposal device 1. Whether the cooperation between the terminal device 3 and the proposal device 1 is executed by the app or the browser is appropriately set by a designer or the like and is not limited here.

[0020] The proposal device 1 is also connected to an information source 7. The information source 7 is an information source capable of providing the information used in the generation process and update process of the life plan executed by the proposal device 1 to the proposal device 1. The number of information sources 7 to which the proposal device 1 is connected and the connection destinations as the information sources 7 are appropriately set by, for example, the designer of the proposal device 1 in consideration of the processing content of the proposal device 1. However, here, at least one of the information sources 7 includes an information source 7 capable of providing the life situation information of the user to the proposal device 1.

[0021] The life situation information of the user is information regarding the life situation of the user. For example, specific examples of the life situation information include purchase history information, search keyword history information on a search site, web site browsing history information, trajectory information of the location information of a mobile terminal, communication history information of a terminal device, ticket purchase history information, billing history information, and the like. The purchase history information of the user includes the usage history of a credit card and the usage history of an EC (Electronic Commerce) site. Further, the ticket purchase history information includes the purchase history of tickets for events such as concerts and the purchase history of tickets (so-called tickets) for using means of transportation such as trains and airplanes. Furthermore, the billing history information is, for example, information on the history of charges made by the user in services provided by application programs via the Internet.

[0022] Furthermore, as another example of the life situation information, information on the posted content posted by the user on an SNS (Social Networking Service), information regarding the physical condition of the user such as the user's medical history (dispensing history) and hospital visit information, schedule information, and the like can also be cited. The schedule information includes, for example, the schedule information held in the user's terminal device and the schedule information managed by a business operator providing a schedule management service.

[0023] As described above, there are various types of user's life situation information. In other words, such life situation information represents the content of the user's actions, and the life situation information includes information on the time (time of day or date) when the user took action. Note that when there is information such as schedule information held in the user's terminal device as the life situation information used by the proposal device 1 for processing, the user's terminal device is set as the information source 7.

[0024] Also, as the information source 7, an information source that can provide the proposal device 1 with life environment information representing the user's life environment, such as information about the user's family, information about income, and information representing the occupation the user has, may be set. Since the user's life environment affects the user's life situation, the user's life environment information may also be considered to be included in the user's life situation information. However, the life environment information may not be information representing the content of the user's actions and may not include time information.

[0025] The proposal device 1 includes an arithmetic device 10 and a storage device 20. The storage device 20 includes a storage medium that stores data and a computer program (hereinafter also referred to as a program) 21. There are multiple types of storage devices in the storage device, such as magnetic disk devices and semiconductor memory elements. Furthermore, there are multiple types of semiconductor memory elements, such as RAM (Random Access Memory) and ROM (Read Only Memory). There are many types in this way. A computer device is equipped with multiple types of storage devices according to the application, but here, for the sake of simplicity, these storage devices will be collectively referred to as the storage device 20 without distinction. Furthermore, the type and number of the storage device 20 included in the proposal device 1 are not limited, and the description thereof is omitted. Note that the proposal device 1 may be connected to a database 5 that is a storage device. In this case, the proposal device 1 may write information to the database 5 or read information from the database 5, but here, to avoid complexity in the description, the description of such cases will be omitted even if they exist.

[0026] The arithmetic unit 10 is composed of a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). By reading and executing the program 21 stored in the storage device 20, the arithmetic unit 10 can have functions based on the program 21. Here, the arithmetic unit 10 has an acquisition unit 11, an expansion unit 12, an estimation unit 13, a planning unit 14, and an output unit 15 as functional units related to the generation and update of the life plan.

[0027] The acquisition unit 11 acquires the user's attribute information and living situation information. The user's attribute information is information representing the user. Here, the user's attribute information is information that can also be paraphrased as personal information or profile information, and is, for example, information such as name, age, address, income, etc. The number and types of the user's attribute information acquired by the acquisition unit 11 are appropriately set by the designer of the proposal device 1, etc., in consideration of, for example, the service content provided by the proposal device 1.

[0028] Here, the method by which the acquisition unit 11 acquires the user's attribute information is not limited, but as an example, a method of acquiring from the user by cooperation with the terminal device 3 can be mentioned. For example, by the cooperation between the proposal device 1 (acquisition unit 11) and the terminal device 3, a screen for inputting attribute information is displayed on the display device 4 of the terminal device 3. When the user inputs attribute information through this display screen, the input attribute information is transmitted from the terminal device 3 to the proposal device 1. The acquisition unit 11 acquires the user's attribute information by receiving the transmitted attribute information.

[0029] Note that the display mode of the screen for inputting user attribute information displayed on the display device 4 can be an appropriate display mode considering, for example, the ease of understanding of the input items for which the user is requested to input information, and is not limited here, so the description thereof is omitted. Further, when acquiring attribute information from the user as described above, a questionnaire may be conducted to acquire information used in the life plan generation process from the user, and the acquisition unit 11 may acquire the answers to the questionnaire. The answers to such a questionnaire may also be used as the user's attribute information.

[0030] Furthermore, instead of acquiring attribute information from the user, for example, the acquisition unit 11 may acquire the user's attribute information from the information source 7. In this case, as the information source 7 to which the acquisition unit 11 is connected, for example, a computer device that manages the user's attribute information is set. As an example of such a computer device, a computer device that controls an administrative system (for example, My Number Portal) that supports searches for administrative procedures such as childcare and nursing care and online applications can be mentioned.

[0031] The acquisition unit 11 associates the acquired user attribute information with the identification information of the user (hereinafter also referred to as user identification information) and stores it in the storage device 20. An example of the timing when the acquisition unit 11 acquires the user's attribute information in this way is when the user starts receiving the life plan proposal service by the proposal device 1.

[0032] The acquisition unit 11 further acquires the user's living situation information. As described above, the user's living situation information is information that represents the living situation of the user. The acquisition unit 11 acquires the user's living situation information from the information source 7 at predetermined timings. The timing at which the acquisition unit 11 acquires the living situation information from the information source 7 may be appropriately set according to the type of living situation information, and is not limited to, but may be, for example, at predetermined time intervals (such as once a month). In addition, if an update notification indicating that the user's living situation information has been updated is set to be transmitted from the information source 7 to the proposal device 1, the acquisition unit 11 may acquire the updated living situation information from the information source 7 upon receiving the update notification. In other words, the timing at which the acquisition unit 11 acquires the living situation information from the information source 7 may be set to be, for example, when the update notification is received from the information source 7.

[0033] The acquiring unit 11 stores the acquired living situation information of the user in the storage device 20 in association with the identification information of the user (user identification information).

[0034] Incidentally, when the acquiring unit 11 acquires user attribute information and living situation information from the information source 7, there are cases where information corresponding to an individual user can be acquired from the information source 7, and cases where the acquiring unit 11 acquires information related to multiple users collectively from the information source 7. When acquiring information related to multiple users collectively from the information source 7, for example, information on each user is acquired as follows.

[0035] For example, assume that information related to multiple users as shown in Fig. 2 is acquired as a collection of information from information source 7. The information shown in the example of Fig. 2 is purchasing information (living situation information) of customers at a certain store. In this example, each transaction data is associated with a transaction ID (Identification) that identifies the transaction data, a user ID that identifies the customer (user), a product ID that identifies the purchased product, the product name, and the purchase date.

[0036] Such a plurality of information (transaction data) is clustered (grouped) by clustering techniques such as K-means or hierarchical clustering. Then, by analyzing features such as purchase patterns for each cluster (group), the characteristics of each user are obtained, and the characteristics are acquired as the user's living situation information. As a specific example of the living situation information in this case, living situation information such as "In January 2023, User A shows a health-oriented purchase behavior, User B purchases foodstuffs in a balanced manner, and User C has a tendency to prefer snacks and fast food" is obtained. Note that the method of extracting the user's living situation information from a plurality of information including information related to a plurality of users is not limited to the method described here, and other methods may be adopted.

[0037] In addition, the acquisition unit 11 may acquire the user's living situation information by acquiring one or more information sources 7 of information publicly available as open data and extracting the user's living situation information from the acquired information. As a method of extracting the user's living situation information from open data in this way, for example, a method of processing open data by database technology using information related to the user is cited as an example.

[0038] When processing open data by database technology, the proposal device 1 may further include a data preprocessing unit 17 as shown by the dotted line in FIG. 1. The data preprocessing unit 17 will explain the technology of adding open data by database technology. For example, the data preprocessing unit 17 may process open data by tagging additional information and attributes to text data using a machine learning model.

[0039] In addition, the data preprocessing unit 17 may use natural language processing technology to perform data structuring, meaning prediction, and similarity evaluation. Thereby, text data or unstructured data may be converted into structured data.

[0040] Note that the formats (data formats) of the attribute information and life situation information acquired by the acquisition unit 11 and stored in the storage device 20 are in formats that are easy for functional units such as the extension unit 12 and the estimation unit 13 to process.

[0041] The extension unit 12 uses the user's attribute information acquired by the acquisition unit 11 to add further attribute information of the user by an information generation method. The information generation method here is a technique for increasing attribute information by estimating attribute information. As an example of the information generation method, there is a method using an attribute information database. In the attribute information database, a plurality of pieces of information that can be attribute information are stored in association. When using the attribute information database, for example, the extension unit 12 searches the attribute information database for information corresponding to the user's attribute information acquired by the acquisition unit 11. When the extension unit 12 finds information corresponding to the user's attribute information in the attribute information database by the search, the extension unit 12 reads out the information associated with the found information from the attribute information database as the estimated user's attribute information. Then, the extension unit 12 adds the information read out from the attribute information database to the user's attribute information as further attribute information of the user. That is, the extension unit 12 stores the further attribute information of the user in the storage device 20 in association with the user identification information in the same manner as other attribute information.

[0042] Another example of the information generation method is a method using a language model based on AI technology. The language model here is a language model learned by a machine learning algorithm for attribute information, and it is possible to output estimated additional attribute information in response to the input of a query for content that requests additional attribute information. When using such a language model, the extension unit 12 generates attribute information as follows to add (extend) the attribute information.

[0043] For example, as a template for a query input to a language model, a query (text) such as "What are the user attributes associated with {attribute}?" is given in advance. User attribute information is input into {attribute} in the template. More specifically, assume that information about the occupation of engineer, which is one of the user's attribute information, is acquired by the acquisition unit 11 and stored in the storage device 20. The expansion unit 12 reads, from the storage device 20, for example, the occupation information "engineer", which is the user's attribute information, and inputs the read attribute information into {attribute} of the query template, thereby generating a query "What are the user attributes associated with engineer?" as input information to the language model. The expansion unit 12 inputs the generated query into the language model, and acquires, as additional attribute information estimated by the language model, the output information from the language model corresponding thereto. Specifically, for example, in response to the input of the query "What are the user attributes associated with engineer?", the language model outputs (answers) information such as "programming", "software development", and "system design". The expansion unit 12 stores, in the storage device 20, in association with the user identification information of the user to whom the attribute information is to be added, the information output from the language model in this way, as additional attribute information estimated by the language model, that is, adds it. When a plurality of attribute information is stored in the storage device 20 as attribute information, the expansion unit 12 sequentially executes the same information generation process for attribute addition while replacing the attribute information one by one.

[0044] The language model calculates the appearance probability of words (attribute information) related to the query which is the input information, and outputs words (attribute information) with a high appearance probability (for example, an appearance probability equal to or higher than a threshold value) as additional attribute information. Therefore, the additional attribute information output from the language model is not limited to one, and may be plural as in the above-described specific examples. Also, even if the same query is input to the same language model, the output from the language model is not necessarily the same. Utilizing this fact, for example, the extension unit 12 may obtain additional attribute information which is a plurality of different output information by repeatedly inputting the same query to the same language model. Furthermore, the language model used by the extension unit 12 may be set to output, as output information, information on the appearance probability associated with the additional attribute information.

[0045] Also, the above-described information generation method is an example, and the information generation method used by the extension unit 12 is not limited to the above-described information generation method as long as it is a technique capable of adding (extending) further attribute information using the acquired attribute information.

[0046] The extension unit 12 repeatedly executes the extension process of the attribute information at preset timings using the attribute information including the attribute information added by the above-described information generation process. By such processing of the extension unit 12, the user's attribute information increases.

[0047] The estimation unit 13 estimates the life events likely to occur to the user and the timing thereof using the user's attribute information and life situation information including the added attribute information. A life event is an event in which the life situation is considered to change significantly in life, and specific examples include marriage, childbirth, children's school enrollment, serious illness, job transfer, etc. Also, moving, purchasing a car or a house, etc. may also be included in the life events.

[0048] There are various methods for estimating life events that are likely to occur (or be experienced) by a user and the timing thereof using the user's attribute information and life situation information. For example, as one example, there is a method using a language model. In this method, for example, the user's life situation information (such as purchase history, search keywords, and words or phrases (sentences) that are search results) is learned by the language model. Then, when a query asking about life events that are likely to occur to the user is input into the language model, information representing the life events that are likely to occur is output as an estimation result from the language model. The timing of occurrence of the life events that are likely to occur is estimated by analyzing the user's life situation information while paying attention to terms related to the life events. Through such estimation processing, for example, an estimation result such as that a life event of changing jobs is likely to occur within several months is output from the estimation unit 13.

[0049] Also, as another example of an estimation method, there is a method using a classification model based on AI technology. In this estimation method, for example, using a plurality of information (features such as age, purchase history, search keyword history) selected from the user's attribute information and life situation information, a plurality of life events are classified into a group that the user is likely to experience and a group that the user is not likely to experience. Further, for the life events in the group that the user is likely to experience, it is determined whether the timing of occurrence (experience time) is close (for example, within one year) using the user's life situation information, and the timing of occurrence (experience time) is estimated such that if it is close, the timing of occurrence (experience time) is inferred.

[0050] Furthermore, as another method for estimating life events, there is a method using clustering technology. In this method, for example, using information such as purchase history and website browsing history, which are information on the user's living situation, a plurality of users are clustered to generate groups of users who perform similar purchase actions and website browsing actions. Then, for each group, life events that are likely to occur (be experienced) in common to the users are estimated. Furthermore, for each user, an estimation (speculation) of the occurrence time (experience time) is performed for the life events estimated to be likely to occur, using the living situation information.

[0051] Furthermore, as another method for estimating life events, there is a rule-based method. In this method, for example, for each life event, information on related terms is given as event-related terms. Then, it is determined whether terms corresponding to the event-related terms are included in the text data included in the user's living situation information (such as purchase history and website browsing history). As a result, when terms corresponding to the event-related terms are included, it is estimated that the occurrence time of the life event related to the included event-related terms is near. Furthermore, for the life events estimated to have a near occurrence time, an estimation (speculation) of the occurrence time is performed using the living situation information.

[0052] Furthermore, as another method for estimating life events, there is a method using the number of terms extracted from the text data included in the user's living situation information. In this method, for example, as described above, for each life event, information on related terms is given as event-related terms. Then, when there are terms corresponding to the event-related terms among the terms extracted from the text data included in the user's living situation information, the number of occurrences of the terms is counted. A life event related to a term whose count number is equal to or greater than a threshold value is estimated as an event with a near occurrence time. Furthermore, for the life events estimated to have a near occurrence time, an estimation (speculation) of the occurrence time is performed using the living situation information.

[0053] Furthermore, as another method for estimating life events, for example, there is a method of analyzing time-series data acquired as the user's life situation information. In this method, for example, when it is detected that the number of occurrences of event-related terms included in the time-series data has increased rapidly by analyzing the time-series data acquired as the user's life situation information, the life event related to the detected event-related term is estimated as an event with a recent occurrence time. Furthermore, for the life event estimated to have a recent occurrence time, an estimation (estimation) of the occurrence time is performed, such as speculating the occurrence time using the life situation information.

[0054] As described above, there are various methods for estimating life events that are likely to occur (likely to be experienced) by the user and their timing. Here, the estimation method adopted by the estimation unit 13 is appropriately set by the designer of the proposal device 1 or the like in consideration of the type, number, and number of users of the information acquired as the user's life situation information, and is not limited.

[0055] In addition, the estimation unit 13 may adopt a plurality of estimation methods, and estimate the life events that are likely to occur to the user and their occurrence times using each estimation method. In this way, when estimating the occurrence of a life event and its occurrence time using a plurality of estimation methods, for example, the certainty (reliability) of the estimation result may differ depending on the type of estimation method. From this, for example, when estimating the occurrence of a life event and its occurrence time using a plurality of estimation methods respectively, it is conceivable to associate information on the certainty (reliability) of the estimation result with the estimation result (information representing the life event estimated to be likely to occur and the estimated time of its occurrence).

[0056] Note that when the appearance probability information as described above is associated with the attribute information added to the extension unit 12, the estimation unit 13 may determine whether to use the attribute information in the estimation process using the appearance probability and the content of the life situation information.

[0057] The estimation unit 13 stores the estimation result obtained by the above-described estimation process in the storage device 20 in association with the user identification information of the corresponding user. Note that information on the estimation result stored in the storage device 20 is associated with, for example, information on the time when the estimation process was executed.

[0058] The planning unit 14 generates a life plan for the user using the user's attribute information, for example, triggered by a request for generating a life plan from the terminal device 3 due to a user operation. A life plan is a lifelong life design. For example, it is a life plan (design drawing) in which the estimated occurrence time of life events, the estimated transition of income and expenditure, the transition of asset status, the change in family composition, etc. are associated with age. Various forms of life plans have been proposed, and there are also various generation methods. Here, since the form of the life plan and its generation method are not limited, the description thereof is omitted. Also, the types of attribute information acquired from the user are set in consideration of information related to the user used in the life plan generation process executed by the planning unit 14.

[0059] The planning unit 14 further updates (generates) the user's life plan using the information on the life events estimated by the estimation unit 13 at a predetermined update timing. The update timing here is, for example, the timing triggered by the fact that such an estimation result has been obtained when the occurrence of a life event has been estimated by the estimation unit 13 for each user. Note that there may be a case where a life event estimated by the estimation unit 13 as likely to occur has already been incorporated into the life plan. In such a case, for example, the update timing may be the timing triggered by detecting that the estimated occurrence time of the life plan and the occurrence time of the life plan reflected in the life plan deviate from each other beyond the allowable range.

[0060] Also, at each predetermined time interval, for each user, it is determined whether there is a life event estimated by the estimation unit 13 that is likely to occur during that time interval, and the timing triggered by the determination that there is an estimated life event may be the update timing.

[0061] That is, here, the update process of the life plan by the planning unit 14 is not performed in response to an update request from the user, but is executed when the occurrence and occurrence time of a new life event of the user are estimated by the respective processes of the acquisition unit 11, the expansion unit 12, and the estimation unit 13.

[0062] The method by which the planning unit 14 updates the life plan is not limited here. For example, there are methods such as regenerating the life plan using the information of the life event estimated by the estimation unit 13, or updating the life plan with reference to the life plans of other users whose life event occurrence times are similar.

[0063] When the occurrence of a plurality of life events is estimated by the estimation unit 13, for example, the planning unit 14 updates the life plan using the life event selected according to a predetermined rule from among those estimated plurality of life events.

[0064] The life plan generated and updated by the planning unit 14 is stored in the storage device 20 in association with the user identification information of the user corresponding to the life plan.

[0065] The output unit 15 outputs the newly generated life plan or the updated life plan by the planning unit 14 to the terminal device 3. That is, when the planning unit 14 generates a life plan in response to a life plan generation request from the terminal device 3, the output unit 15 returns the generated life plan to the terminal device 3. Also, when a request for providing an updated version of the life plan is sent from the terminal device 3 to the proposal device 1, the output unit 15 returns the updated life plan by the planning unit 14 to the terminal device 3 in response to the providing request. In this way, when the output unit 15 outputs the life plan to the terminal device 3, it outputs the life plan in response to a request from the terminal device 3 (in other words, the user).

[0066] By the way, as described above, the update process of the life plan by the planning unit 14 is not executed in response to a request from the user, but is executed in response to the processing results of the acquisition unit 11, the extension unit 12, and the estimation unit 13. That is, the update process of the life plan is performed where the user is not aware. Therefore, as one of its functions, when the planning unit 14 generates an updated life plan, the output unit 15 outputs a notification (hereinafter also referred to as an update notification) informing the terminal device 3 of the user whose life plan has been updated that the life plan has been updated. The output method of this update notification is not limited, but for example, there is a method using communication means such as e-mail or chat. Also, as an output method of the update notification, there is a method in which the update notification is output from the proposal device 1 to the terminal device 3 by the cooperative operation of the proposal device 1 (output unit 15) and the terminal device 3.

[0067] When an update notification is output to the terminal device 3 by the cooperation operation of the proposal device 1 and the terminal device 3, the terminal device 3 notifies the user of the update notification as follows. For example, when the user is operating the terminal device 3 for information search, document creation, etc., the display control function of the terminal device 3 causes a life plan update notification as shown in FIG. 3 to be displayed on the display screen of the display device 4 by a pop-up screen (pop-up window) 41. On the pop-up screen 41, for example, an icon 42 for confirmation is displayed. The icon 42 includes address information of a connection destination for connecting to a web page for viewing the updated life plan. By using this icon 42, the user can display a web page for viewing the updated life plan on the screen of the display device 4.

[0068] Also, as a method of notifying the user of the update notification, instead of using a pop-up screen, for example, the update notification may be displayed in the screen area 44 of the advertisement column on the screen 43 for displaying search results on a search site as shown in FIG. 4. In such a case, in order for the user not to miss the update notification, for example, a display mode of the characters such as blinking the display of the characters may be adopted.

[0069] Note that various timings can be considered for the notification timing at which the terminal device 3 notifies the user of the life plan update notification. For example, when the terminal device 3 receives the life plan update notification, or when a predetermined notification condition is satisfied after the reception of the life plan update notification, etc. are examples of the notification timing. The notification condition is not limited, but as an example, there is a condition such as when browsing a website related to a life event. The notification timing of the life plan update notification may be preset by the designer of the proposal device 1, or may be selected by the user from among a plurality of notification timings preset by the designer of the proposal device 1.

[0070] As described above, the proposal device 1 of the first embodiment is configured. Next, an example of the operation related to the life plan proposal in the proposal device 1 will be described with reference to FIG. 5. FIG. 5 is a flowchart for explaining an example of the operation related to the life plan proposal in the proposal device 1. Also, it can be said that FIG. 5 is a diagram for explaining the life plan proposal method in the proposal device 1.

[0071] For example, it is assumed that in order to receive the life plan proposal service by the proposal device 1, the user registers his / her own attribute information in the proposal device 1 using the terminal device 3. In other words, it is assumed that the acquisition unit 11 acquires the attribute information from the user, and the acquired user attribute information is stored in the storage device 20. Also, it is assumed that the planning unit 14 generates the user's life plan using the user's attribute information, and the life plan is stored in the storage device 20 in association with the user identification information.

[0072] In such a case, for example, the acquisition unit 11 acquires the user's life situation information at a predetermined timing (step 101 in FIG. 5). Also, the expansion unit 12 expands (adds) the user's attribute information using the information generation method with the user's attribute information (step 102).

[0073] The estimation unit 13 estimates the life events likely to occur to the user and the occurrence times thereof using the attribute information including the life situation information acquired by the acquisition unit 11 and the attribute information added by the expansion unit 12 (step 103).

[0074] When the occurrence and the occurrence time of the life event are estimated by the estimation unit 13, the planning unit 14 updates the user's life plan using the information on the estimated life event as well (step 104). As a result, the output unit 15 outputs a life plan update notification to the user's terminal device 3 (step 105).

[0075] Subsequently, for example, when a request for providing an updated life plan is received from the terminal device 3, the output unit 15 outputs (returns) the updated life plan to the terminal device 3 in response to the request (step 106).

[0076] The proposal device 1 of the first embodiment has the configuration as described above. That is, the proposal device 1 acquires the user's life situation information by the acquisition unit 11, estimates the occurrence of life events and their occurrence times from the life situation information by the estimation unit 13, and updates the user's life plan by the planning unit 14 using the information on the occurrence of the estimated life events and their occurrence times. By having such a configuration, the proposal device 1 can update the life plan without acquiring additional information from the user and without receiving an update request from the user.

[0077] In addition, the proposal device 1 includes an extension unit 12, and the user's attribute information can be added by the extension unit 12. That is, since the user's attribute information used in the estimation process of life events by the estimation unit 13 can be increased, the types of information obtained from the estimation process by the estimation unit 13 can be increased, or the reliability of the information can be enhanced. For example, assume that the information "engineer" of the occupation is acquired as one of the attribute information from the user, and the addition of attribute information by the extension unit 12 has not been performed. In such a case, assume that the estimation unit 13 obtains an estimation result (information) such that life events such as "marriage", "job transfer", or "purchase of a new house" are likely to occur to the user within several months. On the other hand, assume that the attribute information such as "software development" is added by the extension unit 12. As a result, it is suggested by the estimation unit 13 that a user interested in IT (Information Technology) and technology is planning to get married in the near future, and it is also conceivable that an estimation result (information) such as a high possibility of being interested in an innovative wedding experience using VR (Virtual Reality) can be obtained.

[0078] <Other Embodiments> The present disclosure is not limited to the above-described first embodiment and can adopt various embodiments. For example, in the first embodiment, in the process from when the occurrence of a life event is estimated by the estimation unit 13 until the life plan is updated by the planning unit 14, the process is executed without receiving information from the user. In contrast, for example, after estimating the occurrence of a life event, the estimation unit 13 may perform a process of transmitting the estimation result to the terminal device 3 via the output unit 15 and allowing the user to confirm the estimation result. For example, assume that as the estimation result by the estimation unit 13, results such as "The life event'marriage' will occur within several months", "The life event 'job change' will occur within several months", and "The life event 'purchase of a new house' will occur within several months to one year" are obtained. The estimation unit 13 transmits such an estimation result to the user's terminal device 3 and displays it on the display device 4, and allows the user to input information on whether the estimation result is correct. In other words, the estimation unit 13 allows the user to confirm the estimation result. When the estimation unit 13 receives the result of confirmation by the user from the terminal device 3, the received information is associated with the information of the corresponding estimation result. When presenting the estimation result by the estimation unit 13, if the estimation unit 13 calculates the certainty (reliability) of the estimation result, the information on the certainty (reliability) of the estimation result may also be presented.

[0079] When the confirmation of the estimation result is thus made by the user, for example, the planning unit 14 updates the life plan using the information on the life event that has been confirmed to occur by the user.

[0080] Also, although the proposal device 1 of the first embodiment includes the planning unit 14, for example, when the plan generation device 9 as shown in FIG. 6 can cooperate with the proposal device 1, the planning unit 14 in the proposal device 1 may be omitted. The plan generation device 9 is a computer device and includes a planning unit having the same function as the planning unit 14 as a functional unit of the arithmetic device (processor) 90.

[0081] Furthermore, the proposed device 1 may be provided with a learning unit 16 as shown in FIG. 7 as a functional unit of the arithmetic device (processor) 10. The learning unit 16 accumulates information and learns a model based on AI technology using a machine learning algorithm in order to improve the accuracy of the estimation by the estimation unit 13. Note that the proposed device 1 shown in FIG. 7 has the same configuration as that shown in FIG. 1, but illustration of functional units such as the acquisition unit 11 and the expansion unit 12 and the storage device 20 is omitted.

[0082] For example, the estimation result estimated by the estimation unit 13 (that is, the estimation result of the occurrence of the life event and its occurrence time) is transmitted from the proposed device 1 to the user's terminal device 3, and information on the correctness of the estimation result is obtained from the user using the screen display of the display device 4 of the terminal device 3. The learning unit 16 stores the correctness information indicating the correctness of the estimation result obtained from the user in the storage device 20 in association with the corresponding estimation result. In other words, the learning unit 16 attaches a correct label or an incorrect label to the information on the estimation result by the estimation unit 13 using the correctness information obtained from the user.

[0083] Furthermore, the learning unit 16 generates learning information by associating the estimation result with the correctness information and the life situation information used in the estimation process from which the estimation result was derived. Furthermore, as a learning process using the learning information, for example, the learning unit 16 adds information on the degree of relationship between the life event and the event-related term to the relationship data between the life event and the event-related term given in advance (that is, the information related to the process of the estimation unit 13). When the estimation unit 13 estimates the occurrence of a life event using a rule-based method, the accuracy of the estimation result by the estimation unit 13 can be improved by using the information on the event-related term to which such information on the degree of relationship is added.

[0084] In addition, when the estimation unit 13 uses a classification model or a clustering model, the learning unit 16 performs learning processing using the learning information generated as described above, and learns the model used by the estimation unit 13 by a machine learning algorithm. Thereby, the estimation result by the estimation unit 13 can be improved. Note that the model used by the estimation unit 13 can also be said to be information related to the processing of the estimation unit 13.

[0085] Furthermore, in the first embodiment, the processing related to the life plan proposal service is mainly executed by the proposal device 1. In contrast, the plurality of processes related to the life plan proposal service described in the first embodiment may be distributed by cooperation of a plurality of computer devices including, for example, the terminal device 3. For example, as shown in FIG. 8, the terminal device 3 may have the function of the acquisition unit 11. Further, as shown in FIG. 9, the terminal device 3 may have the functions of the acquisition unit 11 and the extension unit 12. Further, as shown in FIG. 10, the terminal device 3 may have the functions of the acquisition unit 11, the extension unit 12, and the estimation unit 13. Further, as shown in FIG. 11, the terminal device 3 may have the functions of the acquisition unit 11, the extension unit 12, the estimation unit 13, the planning unit 14, and the output unit 15. That is, in this case, the terminal device 3 can also be regarded as the proposal device 1, and the output unit 15 outputs the life plan information by, for example, performing display control of the display device 4. Furthermore, as shown in FIG. 12, the terminal device 3 has a functional unit that executes the main process of the process related to the life plan proposal service, and on the computer device side (server side) to which the terminal device 3 is connected via the information communication network, a functional unit (acquisition unit 11) for acquiring information may be provided.

[0086] In the case of distributed processing, the processing is not necessarily shared among a plurality of computer devices in units of functional parts such as the acquisition unit 11, the expansion unit 12, and the estimation unit 13 described in the first embodiment. Instead, the processing may be further subdivided and shared among a plurality of computer devices. In such a case, for example, an acquisition means for acquiring attribute information representing a user and life situation information regarding the user's life situation, an expansion means for adding further attribute information of the user by an information generation method using the acquired attribute information, and an estimation means for estimating a likely life event and its timing for the user using the user's attribute information including the added attribute information and the life situation information are configured by a plurality of computer devices.

[0087] Also, FIGS. 8 to 12 can be said to represent a configuration example of an embodiment of the life plan proposal system in the present disclosure.

[0088] Furthermore, the life plan proposal device according to the present disclosure can also adopt a configuration as shown in FIG. 13. For example, the life plan proposal device 100 shown in FIG. 13 is, for example, a computer device, and includes an acquisition unit 101, an expansion unit 102, an estimation unit 103, and an output unit 104 as functional parts realized by executing a computer program. The acquisition unit 101 acquires attribute information representing a user and life situation information regarding the user's life situation. The expansion unit 102 adds further attribute information of the user by an information generation method using the acquired attribute information. The estimation unit 103 estimates a likely life event and its timing for the user using the user's attribute information including the added attribute information and the life situation information. The output unit 104 outputs a life plan generated using the information on the estimated life event. Note that the acquisition unit 11, the expansion unit 12, the estimation unit 13, and the output unit 15 described in the first embodiment are examples of the acquisition unit 101, the expansion unit 102, the estimation unit 103, and the output unit 104.

[0089] The life plan proposal device 100 has the configuration as described above. An example of the operation in this life plan proposal device 100 will be described with reference to FIG. 14. Note that FIG. 14 is a flowchart for explaining an example of the operation in the life plan proposal device 100, and is also a diagram for explaining an example of the life plan proposal method by the life plan proposal device 100.

[0090] For example, the acquisition unit 101 of the life plan proposal device 100 acquires attribute information representing the user and life situation information regarding the user's life situation (step 201). Using the attribute information thus acquired, the extension unit 102 adds further attribute information of the user by an information generation method (step 202). Also, using the user's attribute information and life situation information including the added attribute information, the estimation unit 103 estimates the life events likely to occur to the user and the timing thereof (step 203). Then, the output unit 104 outputs a life plan generated using the information on the estimated life events (step 204).

[0091] Since the life plan proposal device 100 has the configuration as described above, it can achieve the effect of being able to propose a life plan suitable for the current situation of the user even without information from the user.

[0092] Some or all of the above embodiments may be described as follows in the appended claims, but are not limited thereto. [Appendix 1] An acquisition unit that acquires attribute information representing a user and life situation information regarding the user's life situation, An extension unit that adds further attribute information of the user by an information generation method using the acquired attribute information, An estimation unit that estimates life events likely to occur to the user and the timing thereof using the user's attribute information and life situation information including the added attribute information, An output unit that outputs a life plan generated using the information on the estimated life events A life plan proposal device comprising: [Appendix 2] Further comprising a planning unit that generates a user's life plan using the information on the timing of the presumed life event The life plan proposal device according to Appendix 1 [Appendix 3] The information generation method is a technique that uses a language model that outputs attribute information in response to the input of a query including the acquired attribute information The life plan proposal device according to Appendix 1 [Appendix 4] Further comprising a learning unit that uses information associated with correct / incorrect information about the information of the presumed life event as learning information and executes a learning process for information related to the processing of the presumption unit The life plan proposal device according to Appendix 1 [Appendix 5] The acquisition unit acquires a collection of information including life situation information about a plurality of users, groups the life situation information of the plurality of users in the collection of information using clustering technology, and acquires the life situation information of each user using the characteristics analyzed for each group The life plan proposal device according to Appendix 1 [Appendix 6] The presumption unit acquires information from the user as to whether the information of the presumed life event is correct The life plan proposal device according to Appendix 1 [Appendix 7] The correct / incorrect information about the information of the presumed life event is acquired from the user The life plan proposal device according to Appendix 4 [Appendix 8] Acquisition means for acquiring attribute information representing a user and life situation information regarding the user's life situation, Expansion means for adding further attribute information of the user by an information generation method using the acquired attribute information, Presumption means for presuming a life event likely to occur to the user and its timing using the attribute information of the user including the added attribute information and the life situation information, Output means for outputting a life plan generated using the information of the presumed life event A life plan proposal system comprising [Appendix 9] By a computer, Obtain attribute information representing the user and life situation information regarding the user's life situation, Using the obtained attribute information, add further attribute information of the user by an information generation method, Using the attribute information of the user and the life situation information including the added attribute information, estimate the life events likely to occur to the user and the timing thereof, Output a life plan generated using the information of the estimated life events A life plan proposal method. [Appendix 10] The process of obtaining attribute information representing the user and life situation information regarding the user's life situation, The process of adding further attribute information of the user by an information generation method using the obtained attribute information, The process of estimating the life events likely to occur to the user and the timing thereof using the attribute information of the user and the life situation information including the added attribute information, The process of outputting a life plan generated using the information of the estimated life events A computer program for causing a computer to execute

[0093] Note that part or all of the configurations described in Appendices 2 to 7 subordinate to Appendix 1 described above may be subordinate to Appendices 8, 9, and 10 in the same subordinate relationship as Appendices 2 to 7. Furthermore, not limited to Appendices 1, 8, 9, and 10, within the scope not departing from the above-described embodiments, part or all of the configurations described as appendices can similarly be made subordinate to various hardware, software, various recording means for recording software, or systems.

[0094] Although the present disclosure has been described with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. And each embodiment can be combined with other embodiments as appropriate.

Description of Reference Numerals

[0095] 1 Proposal device 11, 101 Acquisition unit 12, 102 Expansion unit 13, 103 Estimation unit 14 Planning unit 16 Learning unit 100 Life plan proposal device

Claims

1. An acquisition unit that acquires attribute information representing a user and life situation information regarding the user's life situation; An extension unit that adds further attribute information of the user by an information generation method using the acquired attribute information; An estimation unit that estimates a likely life event and its timing for the user using the user's attribute information and life situation information including the added attribute information; An output unit that outputs a life plan generated using the information on the estimated life event A life plan proposal device comprising the above.

2. The life plan proposal device according to claim 1, further comprising a planning unit that generates a life plan for the user using the information on the timing of the estimated life event. The life plan proposal device according to claim 1.

3. The information generation method is a method using a language model that outputs attribute information in response to an input of a query including the acquired attribute information. The life plan proposal device according to claim 1.

4. The life plan proposal device according to claim 1, further comprising a learning unit that executes a learning process of information related to the processing of the estimation unit using, as learning information, information associated with correct / incorrect information about the information on the estimated life event. The life plan proposal device according to claim 1.

5. The acquisition unit acquires a collection of information including life situation information about a plurality of users, groups the life situation information of the plurality of users in the collection of information using clustering technology, and acquires the life situation information of each user using the characteristics analyzed for each group. The life plan proposal device according to claim 1.

6. The estimation unit acquires from the user information on whether the information on the estimated life event is correct. The life plan proposal device according to claim 1.

7. The correct / incorrect information about the information on the estimated life event is acquired from the user. The life plan proposal device according to claim 4.

8. An acquisition means that acquires attribute information representing a user and life situation information regarding the user's life situation; An extension means that adds further attribute information of the user by an information generation method using the acquired attribute information; An estimation means that estimates a likely life event and its timing for the user using the user's attribute information and life situation information including the added attribute information; An output means that outputs a life plan generated using the information on the estimated life event A life plan proposal system comprising the above.

9. By a computer Obtain attribute information representing a user and life situation information regarding the user's life situation, Using the obtained attribute information, add further attribute information of the user by an information generation method, Using the attribute information of the user including the added attribute information and the life situation information, estimate the life events likely to occur to the user and the timing thereof, Output a life plan generated using the information of the estimated life events Life plan proposal method.

10. A process of obtaining attribute information representing a user and life situation information regarding the user's life situation, A process of adding further attribute information of the user by an information generation method using the obtained attribute information, A process of estimating the life events likely to occur to the user and the timing thereof using the attribute information of the user including the added attribute information and the life situation information, A process of outputting a life plan generated using the information of the estimated life events A computer program for causing a computer to execute.

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