Information management system, information management method, and program

Abstract

When generating behavioral modification content, consideration is given to whether or not user information needs to be acquired. [Solution] The information management system includes a content generation unit that inputs user information about a user into a content generation model that generates behavior change content that causes the user to perform a predetermined target behavior by inputting obtainable first user information included in the user information to generate the behavior change content, a contribution evaluation unit that evaluates the contribution of the first user information to the generation of the behavior change content based on a contribution evaluation rule that evaluates the contribution of the first user information to the generation of the behavior change content, and an acquisition necessity determination unit that decides whether or not to acquire the first user information based on the contribution.

Description

[Technical Field]

[0001] The present invention relates to an information management system, an information management method, and a program. [Background technology]

[0002] In recent years, efforts to utilize approaches based on theories of behavioral science, which is the scientific study of human behavior, in service development have been expanding in various fields, including public policy, medicine, retail, and education. Systems that technically support behavioral change and habit formation for subjects in these various fields are also being considered (for example, Patent Document 1).

[0003] The system described in Patent Document 1 analyzes behavioral data containing various data measured on the behavior of multiple subjects, and based on the results of the analysis of the behavioral data, defines a stage index, which is an index used as a standard for multiple stages that gradually lead to a behavior that is a goal for habituation, and each of the multiple stages according to the stage index. For each pair of adjacent stages, it identifies the gap between the two stages that make up the pair. For each stage pair, it identifies reasons / measures that are at least one of the reason for the identified gap and measures to cause a subject belonging to the lower stage to undergo behavioral change to transition to the higher stage from relationship information that defines the relationship between the gap and the reasons / measures, and executes processing related to the identified reasons / measures for each stage pair. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2020-140596 Summary of the Invention [Problem to be solved by the invention]

[0005] However, when generating behavior change content that encourages behavior change, user information about users (target individuals) may be acquired carelessly in order to generate higher quality behavior change content. Acquiring user information carelessly may result in a lack of protection of user privacy and may also result in significant costs for acquiring and managing user information.

[0006] Therefore, an object of the present invention is to consider whether or not it is necessary to acquire user information when generating behavior modification content. [Means for solving the problem]

[0007] An information management system according to one embodiment of the present invention includes a content generation unit that inputs user information about a user into a content generation model that generates behavior change content that causes the user to perform a predetermined target behavior by inputting obtainable first user information included in the user information, and generates behavior change content; a contribution evaluation unit that evaluates the contribution of the first user information to the generation of the behavior change content based on a contribution evaluation rule that evaluates the contribution of the first user information to the generation of the behavior change content; and an acquisition necessity determination unit that determines whether or not to acquire the first user information based on the contribution. [Effects of the Invention]

[0008] According to the present invention, when generating behavior modification content, it is possible to take into consideration whether or not it is necessary to acquire user information. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing an overview of processing in an information processing system 100 according to an embodiment of the present invention. [Figure 2] FIG. 1 is a diagram showing an example of BCT classification. [Figure 3] 1 is a diagram showing a configuration of an information processing system 100 according to an embodiment of the present invention. [Figure 4] 4 is a flowchart showing an example of processing of the information processing system 100 in the first embodiment. [Figure 5] 10 is a flowchart showing an example of processing of the information processing system 100 according to the second embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of the hardware configuration of a computer 600. DETAILED DESCRIPTION OF THE INVENTION

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will now be described with reference to the accompanying drawings, in which: Figure 1 is a diagram showing an overview of processing in an information processing system 100 according to an embodiment of the present invention;

[0011] As a first example, the information processing system 100 determines whether or not it is necessary to acquire first user information based on the degree of contribution according to a contribution evaluation rule that evaluates the degree of contribution of the first user information to the generation of behavior modification content.

[0012] In this case, first, the information processing system 100 accepts an application for providing behavior change content from the information processing device 200, and also accepts the provision of first user information (S111). The information processing system 100 inputs the first user information into a content generation model to generate behavior change content (S112). The information processing system 100 evaluates the contribution of the first user information to the generation of the behavior change content based on the contribution evaluation rule (S113). The information processing system 100 determines whether or not to acquire the first user information based on the contribution (S114).

[0013] Then, based on the result of the determination of necessity, the information processing system 100 acquires the first user information determined to be necessary for providing the behavior change content from the information processing device 200 when providing the behavior change content (S115). The information processing system 100 inputs the first user information into a content generation model to generate behavior change content and provides it to the information processing device 200 (S116).

[0014] In this way, information processing system 100 can reduce the amount of user information acquired from users, thereby avoiding the easy acquisition of user information. Easy acquisition of user information includes, for example, acquiring user information that is little effective in generating high-quality behavior change content. By avoiding the easy acquisition of user information, user privacy can be protected, and the entity that acquired the user information (e.g., the administrator of information processing system 100) can reduce the costs of collecting user information and the costs of properly managing the user information.

[0015] In addition, as a second embodiment, the information processing system 100 determines whether or not to acquire update information based on the contribution of the update information for updating the content generation model according to a contribution evaluation rule that evaluates the contribution of the update information to updating the content generation model, and updates the content generation model based on the acquired update information.

[0016] In this case, first, the information processing system 100 receives update information from the information processing device 200 (S121). The information processing system 100 evaluates the contribution of the update information to the update of the content generation model based on the contribution evaluation rule (S122). The information processing system 100 determines whether or not to acquire update information based on the contribution (S123).

[0017] Then, when updating the content generation model, the information processing system 100 acquires update information from the information processing device 200 (S124). The information processing system 100 updates the content generation model based on the update information (S125).

[0018] In this way, the information processing system 100 can reduce the amount of update information acquired when updating a content generation model, thereby preventing the update information from being acquired carelessly. As a result of preventing the update information from being acquired carelessly, the privacy of the user corresponding to the update information can be protected, and the entity that acquired the update information (for example, the administrator of the information processing system 100) can reduce the costs for collecting the update information and the costs for appropriately managing the update information.

[0019] The two information processing devices 200 shown in FIG. 1 may be different information processing devices or may be the same information processing device.

[0020] In this embodiment, behavior change content is content that causes a user to perform a predetermined target behavior (also referred to as behavior change). That is, behavior change content is content that has the effect of changing a user's behavior, for example. In this embodiment, an example is described in which the behavior change content is one piece of behavior change content, but if the behavior change content is a series of pieces of behavior change content, the behavior change content can be appropriately interpreted as a series of pieces of behavior change content.

[0021] Behavior change content is content generated based on, for example, behavior change techniques (BCTs). For example, BCTTv1 (Michie S, Richardson M, Johnston M, et al.: The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med 2013; 46: 81-95.) specifies 93 BCTs in 16 groups. Note that BCTs are not limited to BCTTv1 and may be specified in any way as long as they comprehensively cover behavior change techniques.

[0022] BCTTv1 defines 16 BCT groups: "1. Goals and planning," "2. Feedback and monitoring," "3. Social support," "4. Shaping knowledge," "5. Natural consequences," "6. Comparison of behavior," "7. Associations," "8. Repetition and substitution," "9. Comparison of outcomes," "10. Reward and threat," "11. Regulation," "12. Antecedents," "13. Identity," "14. Scheduled consequences," "15. Self-belief," and "16. Covert learning."

[0023] In BCTTv1, one or more BCTs belong to each of the 16 BCT groups shown in Figure 2. For example, BCTs such as "5.5. Anticipated regret" belong to the BCT group "5. Natural consequences." Also, BCTs such as "10.11. Future punishment" belong to the BCT group "10. Reward and threat." Although not shown, one or more BCTs also belong to the other groups.

[0024] Each BCT has components, and the degree to which each BCT is included in a certain content may be represented as a component value. The sum of the component values ​​of each BCT belonging to the same BCT group may be represented as the component value of the BCT group.

[0025] Examples of behavioral changes promoted by behavior change content include, but are not limited to, language learning, dieting, purchasing financial products offered by financial institutions, regular medical checkups, and use of public services. Furthermore, behavior change content is not limited to content provided to users via electromagnetic means such as applications installed on terminals, web pages, emails, and short messages, but may also be provided to users via other methods (e.g., customer service, mail, etc.). Furthermore, behavior change content may be, but is not limited to, text information related to a specific service (e.g., chat logs), moving images, still images, audio of conversations, application-related data, and the like, and may be any information related to the content of the behavior change.

[0026] When generating and evaluating behavioral change content, a coordinate system is created based on multiple behavioral change factors, and a target coordinate or target area (hereinafter collectively referred to as the target area) is set in this coordinate system. Whether the user has undergone behavioral change is then evaluated based on whether the user's coordinates in the coordinate system have approached the target area. Hereinafter, the distance calculated in this coordinate system will be referred to as the "Behavioral Scientific Distance (BSD)."

[0027] In this coordinate system, by setting the current coordinates and the target area where intervention should be aimed for each user, the behavioral scientific distance from the current coordinates to the target area can be expressed as a multidimensional vector, and the BCT that should be adopted to close this distance can be objectively and clearly visualized. In other words, higher quality behavior change content is, for example, behavior change content that further shortens the behavioral scientific distance from the current coordinates to the target area.

[0028] Behavioral change factors are, for example, factors that cause users to take target actions. Multiple behavioral change factors in a target field can be identified based on academic research or attitude surveys, behavioral science theories, user persona settings, or behavioral process maps. Examples of behavioral change factors include "Capacity," "Opportunity," and "Motivation" in the COM-B model, which is commonly used in behavioral science. Alternatively, as other examples of behavioral change factors, factors defined by the Integrated Behavioral Model (IBM) (also referred to as "IBM factors") include experiential attitude, instrumental attitude, injunctive norm, descriptive norm, perceived control, self-efficacy, knowledge, skills, salience of the behavior, environmental constraints, and habit, and in this embodiment, behavioral change factors including at least two of these may be identified.

[0029] The above-described IBM factors are merely examples, and higher-level factors that encompass the above IBM factors may be identified as behavioral change factors. For example, the experiential attitude and instrumental attitude may be included in "Attitude," the indicative norm and descriptive norm may be included in "Perceived Norm," the sense of behavioral control and self-efficacy may be included in "Personal Agency," the knowledge and skills may be included in "Knowledge," the importance of behavior may be included in "Importance," and environmental constraints may be included in "Friction." Alternatively, lower-level factors obtained by dividing the above IBM factors may be identified as behavioral change factors. In this embodiment, any factors related to human behavioral intentions, such as factors defined in the COM-B model or behavioral models other than IBM, may be adopted as behavioral change factors.

[0030] The likelihood of responding to a behavioral change factor may vary from user to user. That is, one user may be more likely to undergo behavioral change due to behavioral change content that strongly influences a first behavioral change factor, while another user may be more likely to undergo behavioral change due to behavioral change content that strongly influences a second behavioral change factor. Even for the same user, the likelihood of responding to a behavioral change factor may vary depending on the passage of time, the time and environment at which the behavioral change content is administered, and the target behavior and the content of the behavioral change. The likelihood of responding to a behavioral change factor may be expressed as a user's behavioral characteristics. Thus, the behavioral distance within which behavioral change content can be effective may vary depending on the user's behavioral characteristics.

[0031] 3 is a diagram showing the configuration of an information processing system 100 according to one embodiment of the present invention. The information processing system 100 is communicably connected to an information processing device 200 via a network such as the Internet. Details of the information processing system 100 will be described later.

[0032] The information processing device 200 outputs at least one of user information about the user and update information for updating the content generation model to the information processing system 100. The information processing device 200 may be, for example, a computer, a smartphone, a tablet terminal, a personal computer, or the like.

[0033] The information processing device 200 may be a user device used by a user. In this case, the information processing device 200 may output user information to the information processing system 100, but may not output update information.

[0034] Furthermore, the information processing device 200 may be an information management device that manages information. In this case, the information processing device 200 may output update information to the information processing system 100, but may not output user information.

[0035] Although one information processing device 200 is shown in FIG. 3, the information processing device 200 may be a plurality of information processing devices 200 (for example, a user device and an information management device).

[0036] Next, details of the information processing system 100 will be described. The information processing system 100 includes a storage unit 110, an acquisition processing unit 120, an update information acquisition unit 130, a behavioral characteristic acquisition unit 140, a content generation unit 150, a content evaluation unit 160, a contribution evaluation unit 170, an acquisition necessity determination unit 180, a content output unit 190, and a model update unit 195. Each unit shown in Fig. 3 can be realized, for example, by using a storage area or by a processor executing a program stored in the storage area.

[0037] The storage unit 110 stores information to be processed in the information processing system 100. The storage unit 110 can store, for example, user information, update information, behavioral characteristic information, behavioral change content, effect evaluation result information, contribution evaluation result information, and decision result information, which will be described later.

[0038] The acquisition processing unit 120 acquires the user information and stores the acquired user information in the storage unit 110. The acquisition processing unit 120 acquires the user information from the information processing device 200, for example.

[0039] The acquisition processing unit 120 can acquire user information (for example, first user information) that is to be the target of the acquisition necessity determining process before the acquisition necessity determining unit 180 performs the acquisition necessity determining process, which will be described later.

[0040] The acquisition processing unit 120 can perform an acquisition process to acquire user information (for example, first user information) based on the result of the necessity determination by the acquisition necessity determining unit 180. Furthermore, the acquisition processing unit 120 can perform an acquisition process to not acquire user information (for example, first user information) based on the result of the necessity determination by the acquisition necessity determining unit 180.

[0041] The user information includes, but is not limited to, biometric information about the user's body, location information or device information about the user or the device (information processing device 200) owned by the user, and information about the content of the answers to a questionnaire. The biometric information includes, but is not limited to, information about the content of the results of the user's health check and vital information such as the user's heart rate.

[0042] Before the acquisition necessity determination process, the user information acquired as the target of the acquisition necessity determination process may be user information with a larger amount of information (at least one of content and items) than the user information acquired based on the result of the necessity determination. In other words, the information processing system 100 first acquires a wide range of user information that can be acquired, and then further acquires only the user information that is determined to need to be acquired, thereby generating behavior change content to be provided to the user.

[0043] The update information acquisition unit 130 acquires the update information and stores the acquired update information in the storage unit 110 .

[0044] The update information acquisition unit 130 can acquire update information that is to be subjected to the acquisition necessity determination process before the acquisition necessity determination process by the acquisition necessity determining unit 180, which will be described later.

[0045] The update information acquisition unit 130 can perform an acquisition process to acquire update information based on the result of the necessity determination by the acquisition necessity determining unit 180. Furthermore, the update information acquisition unit 130 can perform an acquisition process to not acquire update information based on the result of the necessity determination by the acquisition necessity determining unit 180.

[0046] The update information may be any information that can update the content generation model. The update information may include user information, and may also include behavioral characteristic information, which will be described later.

[0047] Before the acquisition necessity determining process, the update information acquired as the target of the acquisition necessity determining process may be update information with a larger amount of information (at least one of content, type, and items) than the update information acquired based on the result of the necessity determination. In other words, the information processing system 100 can first acquire a wide range of update information that can be acquired, and then further acquire only update information that is determined to need to be acquired, thereby updating the content generation model.

[0048] The behavioral characteristic acquisition unit 140 acquires behavioral characteristic information related to the user's behavioral characteristics, and stores the acquired behavioral characteristic information in the storage unit 110. Here, the behavioral characteristic is, for example, the user's tendency to react to each behavioral change factor.

[0049] The behavioral characteristic information of the same user may be different each time it is acquired by the behavioral characteristic acquisition unit 140. That is, the behavioral characteristic information of the same user may be different depending on the passage of time, the time when the behavioral characteristic acquisition unit 140 acquires the information, the circumstances such as the environment at that time, and the contents of the target behavior and behavioral change.

[0050] The content generation unit 150 generates behavior change content based on a content generation model for generating behavior change content that causes the user to perform a predetermined target behavior, and stores the generated behavior change content in the storage unit 110.

[0051] The content generation model may be, for example, a model that generates behavior change content in response to input of user information. That is, in this case, the content generation unit 150 can input first user information to the content generation model and generate behavior change content (post-input behavior change content). The content generation unit 150 may also generate behavior change content (pre-input behavior change content) without inputting the first user information to the content generation model. Note that in this embodiment, generating behavior change content (pre-input behavior change content) without inputting the first user information means inputting user information that does not include the first user information, i.e., user information different from the first user information, to the content generation model and generating behavior change content (pre-input behavior change content).

[0052] The content generation model may also be a model that generates behavior change content based on the user's behavioral characteristics in response to input of user information and behavioral characteristic information. In other words, in this case, the content generation unit 150 can input user information and behavioral characteristic information to the content generation model and generate behavior change content based on the user's behavioral characteristics.

[0053] The content generation model may also be a model that generates a series of behavior change contents corresponding to each of a plurality of behaviors performed until a predetermined target behavior is achieved, in other words, in this case, the content generator 150 can generate a series of behavior change contents based on the content generation model.

[0054] In addition, the content generation unit 150 can generate behavior change content (updated behavior change content) based on the pre-updated content generation model before being updated by the model update unit 195 described later, and the updated content generation model updated by the model update unit 195.

[0055] The content generation model is, for example, a model that generates behavior change content that has the effect of shortening the behavioral scientific distance from the current coordinates to the target area.

[0056] The content generation model may generate content using, for example, artificial intelligence (AI) technology, particularly, for example, a generation AI. Specifically, when the content generation model receives input of user information, it generates generation request information by incorporating the user information into pre-set generation request information (i.e., a prompt), obtains behavior change content generated by the generation AI using the generated generation request information, and outputs the behavior change content. Here, the generation request information may include, for example, information regarding the target behavior or the content of the behavior change, or information regarding the type of behavior change content to be generated. Furthermore, the generation request information may be generation request information for instructing the generation AI to generate behavior change content that has the greatest effect of shortening the behavioral scientific distance from the current coordinates to the target area.

[0057] The content generation model may also be a model that generates behavior change content by selecting at least one behavior change content from a plurality of pre-defined behavior change content items based on user information, and may select the behavior change content item that has the greatest effect of shortening the behavioral scientific distance from the current coordinates to the target area.

[0058] In addition, the content generation model may, for example, generate one piece of behavior change content by combining behavior change content or elements of behavior change content selected from a plurality of pre-set behavior change content or elements of behavior change content.

[0059] The content generation model may also generate a series of behavior change content pieces made up of multiple pieces of behavior change content pieces.

[0060] The content evaluation unit 160 evaluates the effectiveness of the behavior change content based on content evaluation rules that evaluate the effectiveness of the behavior change content in causing the user to perform a specified target behavior, and stores effect evaluation result information regarding the evaluated effect in the memory unit 110.

[0061] The content evaluation rule may be, for example, correspondence information indicating the correspondence between a plurality of elements for evaluating content and the weight of each element, which are set in advance. Alternatively, the content evaluation rule may be, for example, an evaluation model that inputs content and outputs a score indicating the evaluation result of the content.

[0062] The content evaluation rule may also be a rule that evaluates the magnitude of the behavioral distance at which the behavior change content acts. In other words, in this case, the content evaluation rule may be a rule that more highly evaluates behavior change content that further shortens the behavioral distance to the user's target behavior. The content evaluation rule may be a rule that associates the behavioral distance at which the behavior change content acts with the evaluation result.

[0063] Furthermore, the content evaluation rule may be such that, for example, if the content (e.g., text) is general, the quality of the content is evaluated as low, and if the content (e.g., text) is distinctive, the quality of the content is evaluated as high. Here, whether the content is distinctive or not may be evaluated based on, for example, the proportion of proper nouns contained in the content, i.e., the higher the proportion of proper nouns contained in the content, the more distinctive the content may be evaluated to be.

[0064] Furthermore, the content evaluation rules may evaluate content as being of high quality if, for example, the similarity of meaning between the sentences is low and the density of information is high, if the proportion of kanji and hiragana used is appropriate and the sentences are highly readable, if the content is appropriate for the context even when translated into another language, or if the content includes fonts, sizes, shapes, or colors that take universal design into consideration.

[0065] Based on the content evaluation rules, the content evaluation unit 160 can output, as an evaluation result, for example, a quantitative score indicated using a numerical value (e.g., a score according to behavioral science distance) or a qualitative score (e.g., "very good", "good", etc.).

[0066] The content evaluation unit 160 can evaluate the effectiveness of the post-input behavior change content based on the content evaluation rules. Also, the content evaluation unit 160 can evaluate the effectiveness of the pre-input behavior change content based on the content evaluation rules. Also, the content evaluation unit 160 can evaluate the effectiveness of a series of post-input behavior change content generated by inputting the first user information into a content generation model.

[0067] The content evaluation unit 160 can evaluate the effectiveness of the updated behavior change content based on the content evaluation rules. Also, the content evaluation unit 160 can evaluate the effectiveness of the behavior change content (pre-update behavior change content) generated based on the pre-update content generation model based on the content evaluation rules. Also, the content evaluation unit 160 can evaluate the effectiveness of a series of updated behavior change content.

[0068] In this way, the content evaluation unit 160 can evaluate how important the generated behavior change content is for achieving the target behavior.

[0069] The contribution evaluation unit 170 evaluates the contribution of the first user information to the generation of the behavior change content based on a first contribution evaluation rule that evaluates the contribution of the first user information to the generation of the behavior change content, and stores contribution evaluation result information regarding the evaluated contribution in the memory unit 110.

[0070] The contribution evaluation unit 170 can evaluate the contribution of the first user information to the effect evaluated by the content evaluation unit 160.

[0071] Here, the content evaluation section 160 may evaluate the magnitude of the behavioral scientific distance at which the behavior change content acts as the effectiveness of the behavior change content.

[0072] The contribution evaluation unit 170 can evaluate the contribution of the first user information based on the effect of the pre-input behavior change content and the effect of the post-input behavior change content evaluated by the content evaluation unit 160. That is, in this case, the first contribution evaluation rule may be, for example, a rule for evaluating the contribution of the first user information based on the effect of the pre-input behavior change content and the effect of the post-input behavior change content.

[0073] Specifically, first, the content evaluation unit 160 evaluates the effectiveness of the pre-input behavior change content and outputs pre-input effect evaluation result information as the evaluation result. Next, the content evaluation unit 160 evaluates the effectiveness of the post-input behavior change content and outputs post-input effect evaluation result information as the evaluation result. Then, the contribution evaluation unit 170 compares the pre-input effect evaluation result information and the post-input effect evaluation result information to evaluate the contribution of the first user information. In this case, the contribution evaluation unit 170 may evaluate, for example, the difference or discrepancy between the effect (e.g., score) indicated by the pre-input effect evaluation result information and the effect (e.g., score) indicated by the post-input effect evaluation result information as the contribution of the first user information. This allows the contribution evaluation unit 170 to evaluate the contribution of the additional investment of the resource, the first user information, to the return, the evaluation result, from the perspective of ROI (Return on Investment). In other words, the contribution evaluation unit 170 can evaluate the contribution in accordance with the degree to which it is expected that more effective behavior change content will be generated if the first user information is acquired. In this case, the contribution evaluation section 170 can evaluate the contribution from the perspective of how much the first user information contributes to determining behavior change content that is likely to cause the user to achieve the target behavior.

[0074] In this case, the difference between the effect (e.g., score) indicated by the pre-input effect evaluation result information and the effect (e.g., score) indicated by the post-input effect evaluation result information may be the difference in behavioral distance. Consider an example in which the target behavior is commuting to work and the first user information is that the user is at home. In this case, the post-input behavior change content may be, for example, a message such as, "Why don't you leave home?" Since the user's whereabouts are unknown, the pre-input behavior change content may be a message such as, "Why don't you go to work?" rather than a message such as, "Why don't you leave home?" In this case, the behavioral distance at which the message "Why don't you go to work?" has an effect may be greater than the behavioral distance at which the message "Why don't you go to work?" has an effect. This is because, for example, the word "work" may be an obstacle to the user's behavior change. In such a case, the contribution evaluation unit 170 may evaluate, for example, the difference in behavioral distance as the contribution of the first user information, that is, that the user is at home. In this way, the contribution evaluation section 170 can evaluate the degree to which the first user information contributes to generating effective behavior change content from a plurality of expected behavior change content.

[0075] Furthermore, the contribution evaluation unit 170 can evaluate the contribution of the first user information further based on external environment information about an external environment related to the execution of a predetermined target behavior. That is, in this case, the first contribution evaluation rule may be, for example, a rule for evaluating the contribution of the first user information further based on the external environment information.

[0076] In this case, the contribution evaluation unit 170 can evaluate the degree to which the first user information contributes to responding to changes in the environment surrounding the target behavior. Consider an example in which the target behavior is commuting to work, the first user information is the route the user uses for commuting, and the external environment information is the operating status of the train used for commuting. In this case, when the train used for commuting is operating normally, the first user information has a small effect on the generation of behavior change content and the achievement of the target behavior. However, when the train used for commuting is not operating normally, the first user information may have a large effect on the generation of behavior change content and the achievement of the target behavior. This is because, for example, when the train used for commuting is not operating normally, the user may be reluctant to go to work. When the train used for commuting is not operating normally, instead of or in addition to the message "Would you like to leave home?", behavior change content that presents the time until the train used for commuting returns to normal or a detour route different from the route the user normally uses for commuting may be effective. In other words, the first user information, which is the route used by the user for commuting and has a small contribution degree when the schedule is normal, may become the first user information with a high contribution degree when the schedule is abnormal. In this way, the contribution degree evaluation unit 170 can evaluate the contribution degree by further taking into account the external environment information.

[0077] The external environment information may be, for example, information about a change in the environment surrounding the target behavior, such as a scandal at the user's workplace being reported in the news, but is not limited to this.

[0078] The contribution evaluation unit 170 evaluates the contribution of the update information to the content generation model based on a second contribution evaluation rule that evaluates the contribution of the update information to the update of the content generation model, and stores contribution evaluation result information regarding the evaluated contribution in the memory unit 110.

[0079] The contribution evaluation unit 170 can evaluate the contribution of the update information to the content generation model based on the effect of the pre-update behavior change content and the effect of the post-update behavior change content. That is, in this case, the second contribution evaluation rule may be a rule that evaluates the contribution based on the effect of the pre-update behavior change content and the effect of the post-update behavior change content. Here, the information input to the content generation model in the pre-update behavior change content and the post-update behavior change content may be the same. That is, the difference between the pre-update behavior change content and the post-update behavior change content may be the difference in the content generation model, in other words, the difference between the pre-update content generation model and the post-update content generation model.

[0080] Specifically, first, the content evaluation unit 160 evaluates the effectiveness of the pre-update behavior change content and outputs pre-update effect evaluation result information as the evaluation result. Next, the content evaluation unit 160 evaluates the effectiveness of the post-update behavior change content and outputs post-update effect evaluation result information as the evaluation result. Then, the contribution evaluation unit 170 compares the pre-update effect evaluation result information with the post-update effect evaluation result information to evaluate the contribution of the update information to the content generation model. At this time, the contribution evaluation unit 170 may evaluate, for example, the difference or discrepancy between the effect (e.g., score) indicated by the pre-update effect evaluation result information and the effect (e.g., score) indicated by the post-update effect evaluation result information as the contribution of the update information to the content generation model. In this way, the contribution evaluation unit 170 can evaluate the contribution of the additional investment of resources, namely the update information, to the return of updating (i.e., improving) the content generation model from the perspective of ROI (Return on Investment). In other words, when the contribution evaluation unit 170 acquires the update information, it can evaluate the contribution according to the degree to which it is expected that the pre-update content generation model can be updated to an updated content generation model that can generate more effective behavior change content. In this case, the contribution evaluation unit 170 can evaluate the contribution from the perspective of how much the update information contributes to updating the content generation model that generates behavior change content that is likely to cause the user to achieve the target behavior.

[0081] In this case, the difference between the effect (e.g., score) indicated by the pre-update effect evaluation result information and the effect (e.g., score) indicated by the post-update effect evaluation result information may be the difference in behavioral science distance. In this way, the contribution evaluation unit 170 can evaluate the degree to which the update information contributes when updating the pre-update content generation model to an updated content generation model capable of generating more effective behavior change content. For example, if the target behavior is commuting to work, it is conceivable to register the user's workplace (e.g., the company the user belongs to) as update information. By registering the user's company, it is possible to include a specific station name related to the workplace (e.g., the nearest station to the workplace) in the behavior change content. If the behavior change content before the update did not include a station name but the updated behavior change content does include a station name, it may be possible to switch whether to acquire workplace information as update information from the user depending on whether the evaluation result after the update is higher than the evaluation result before the update by a certain amount.

[0082] Furthermore, the contribution evaluation unit 170 can evaluate the contribution of the update information to the content generation model further based on the external environment information. That is, in this case, the second contribution evaluation rule may be, for example, a rule that evaluates the contribution of the update information to the content generation model further based on the external environment information. For example, if the target behavior is commuting to work, and the user has registered information about the company to which the user belongs, the location where the user commutes to work may change due to an office relocation or other reason. By acquiring information about the relocation of the user's company as external environment information, it may be better to change the station name or other information included in the behavior change content sent to the user.

[0083] The acquisition necessity determining unit 180 determines whether or not it is necessary to acquire the first user information based on the contribution evaluated based on the first contribution evaluation rule, and stores in the storage unit 110 determination result information relating to the determination result.

[0084] Furthermore, the acquisition necessity determining section 180 determines whether or not it is necessary to acquire update information based on the contribution evaluated based on the second contribution evaluation rule, and stores in the storage section 110 determination result information relating to the determination result.

[0085] The decision result information may be, for example, information in which, for each of the first user information and the update information, information indicating "required" indicating that acquisition is necessary or "not required" indicating that acquisition is not necessary is associated.

[0086] For example, the acquisition necessity determining unit 180 may determine that acquisition is necessary when the contribution rate exceeds a predetermined threshold.

[0087] In this way, the acquisition necessity determining unit 180 can determine that it is necessary to acquire first user information that is expected to enable the generation of more effective behavior change content, for example. Also, the acquisition necessity determining unit 180 can determine that it is necessary to acquire update information that is expected to enable the update of a content generation model to be more effective, for example.

[0088] The content output unit 190 outputs behavior change content obtained by inputting the first user information acquired based on the acquisition necessity determined by the acquisition necessity determining unit 180 into the content generation model. This enables the information processing system 100 to output behavior change content generated based on the first user information that is expected to generate more effective behavior change content.

[0089] The content output unit 190 may output the behavior change content to, for example, the information processing device 200. The content output unit 190 may also output the behavior change content to an information processing device used by a person who provides the behavior change content to users.

[0090] The model update unit 195 updates the content generation model by using the update information. The model update unit 195 can update the pre-update content generation model before being updated by the update information by using the update information, and generate an updated content generation model.

[0091] The model update unit 195 can update the content generation model using the update information acquired based on the acquisition necessity determined by the acquisition necessity determining unit 180.

[0092] Furthermore, the model update unit 195 can update the content generation model based on the contribution evaluated by the contribution evaluation unit 170 based on the second contribution evaluation rule. In this case, the model update unit 195 may update the content generation model using update information having a contribution exceeding a predetermined threshold. This allows the information processing system 100 to update the content generation model without the need to further acquire update information, thereby simplifying information processing. Furthermore, in this case, when the content generation model is next updated, the update information acquisition unit 130 may acquire only the update information determined to need to be acquired, and the processing of the second embodiment in the information processing system 100 may be performed. This allows the acquired update information to be selected sequentially.

[0093] Furthermore, the model update unit 195 can update the content generation model using the behavioral characteristic information.

[0094] The first user information may be a plurality of pieces of first user information. In this case, the contribution evaluation unit 170 can evaluate the contribution of each piece of first user information based on the first contribution evaluation rule. Furthermore, the acquisition necessity determination unit 180 can determine whether or not to acquire each piece of first user information based on the contribution of each piece of first user information, and the acquisition processing unit 120 can acquire the first user information that is determined to be required to be acquired from the plurality of pieces of first user information.

[0095] The update information may be a plurality of pieces of update information. In this case, the contribution evaluation unit 170 can evaluate the contribution of each of the plurality of pieces of update information. Furthermore, the acquisition necessity determination unit 180 can determine whether or not each of the plurality of pieces of update information needs to be acquired, and the update information acquisition unit 130 can acquire the update information determined to need to be acquired from the plurality of pieces of update information.

[0096] Next, a specific example of the information processing system 100 will be described.

[0097] FIG. 4 is a flowchart showing an example of processing by the information processing system 100 in the first embodiment.

[0098] First, the acquisition processing unit 120 acquires multiple pieces of user information (S401). Here, the multiple pieces of user information may be, for example, user information of a common type among multiple users (e.g., multiple users belonging to a predetermined group). Next, the content generation unit 150 generates behavior change content based on the multiple pieces of user information, and the content evaluation unit 160 evaluates the generated behavior change content (S402). At this time, the content generation unit 150 may generate behavior change content by inputting all of the multiple pieces of user information into a content generation model, and behavior change content by inputting part of the multiple pieces of user information (e.g., user information included in the multiple pieces of user information is excluded) into the content generation model. Furthermore, the content generation unit 150 may further input behavioral characteristic information acquired by the behavioral characteristic acquisition unit 140 into the content generation model to generate behavior change content. The contribution evaluation unit 170 evaluates the contribution of each piece of user information based on a first contribution evaluation rule (S403). At this time, the contribution evaluation unit 170 may evaluate the contribution of each of the plurality of pieces of user information, for example, based on the effect of the post-input behavior change content and the evaluation of the pre-input behavior change content for each of the plurality of pieces of user information. The acquisition necessity determination unit 180 determines whether or not it is necessary to acquire each of the plurality of pieces of user information (S404).

[0099] Then, based on the result of the necessity determination, the acquisition processing unit 120 performs an acquisition process to acquire user information (e.g., first user information) from among the plurality of pieces of user information, and performs an acquisition process to decide not to acquire user information (e.g., second user information) from among the plurality of pieces of user information (S405). At this time, the types of user information that are acquired and the types of user information that are not acquired may differ for each user. The content generation unit 150 generates behavior change content based on the user information (e.g., first user information) acquired based on the acquisition necessity determination, and the content output unit 190 outputs the behavior change content (S406).

[0100] In this way, information processing system 100 first acquires multiple pieces of user information, determines whether or not to acquire each piece of user information based on the contribution of each piece of user information, and acquires user information determined to need to be acquired (e.g., first user information). That is, for example, when providing behavior change content based on user information, information processing system 100 acquires multiple pieces of user information before providing the behavior change content, identifies user information that needs to be acquired to provide effective behavior change content, and acquires user information determined to need to be acquired (e.g., first user information) to generate and provide the behavior change content. This reduces the amount of user information acquired from users. As a result of reducing the amount of user information acquired from users, user privacy can be protected, and the entity that acquired the user information (e.g., the administrator of information processing system 100) can reduce costs for collecting user information and appropriately managing the user information. Information processing system 100 may also discard previously acquired user information determined not to need to be acquired. This allows the information processing system 100 to avoid the need to manage unnecessary information, reducing the cost of information management and the risk of information leakage.

[0101] FIG. 5 is a flowchart showing an example of processing by the information processing system 100 in the second embodiment.

[0102] First, the update information acquisition unit 130 acquires a plurality of pieces of update information (S501). The contribution evaluation unit 170 evaluates the contribution of each piece of update information to the update of the content generation model based on the second contribution evaluation rule (S502). The acquisition necessity determination unit 180 determines whether or not it is necessary to acquire each piece of update information (S503).

[0103] Then, the update information acquisition unit 130 acquires update information that is determined to need to be acquired from the plurality of pieces of update information based on the result of the necessity determination (S504). The model update unit 195 updates the content generation model using the update information that is determined to need to be acquired and acquired (S505). At this time, the information processing system 100 may discard information that was previously acquired regarding the update information that is determined not to need to be acquired.

[0104] Next, an example of a hardware configuration in which the information processing system 100 is realized by a computer 600 will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the hardware configuration of the computer 600.

[0105] As shown in FIG. 6, a computer 600 includes, for example, a processor 601, a memory 602, a storage device 603, an input I / F unit 604, a data I / F unit 605, a communication I / F unit 606, and a display device 607.

[0106] Computer 600 may be, for example, a server computer, a personal computer (e.g., desktop, laptop, tablet, etc.), a media computing platform (e.g., cable, satellite set-top box, digital video recorder, etc.), a handheld computing device (e.g., PDA, email client, etc.), or any other type of computing or communications platform.

[0107] The processor 601 is a control unit that controls various processes in the computer 600 by executing programs stored in the memory 602 .

[0108] The memory 602 is a storage medium such as a RAM (Random Access Memory), etc. The memory 602 temporarily stores the program code of the program executed by the processor 601 and data required when the program is executed.

[0109] The storage device 603 is a non-volatile storage medium such as a hard disk drive (HDD), flash memory, etc. The storage device 603 stores an operating system and various programs for realizing the above-mentioned configurations.

[0110] The input I / F unit 604 is a device for receiving input from a user. The input I / F unit 604 is, for example, a keyboard, a mouse, a touch panel, various sensors, a wearable device, etc. The input I / F unit 604 may be connected to the computer 600 via an interface such as a USB (Universal Serial Bus).

[0111] The data I / F unit 605 is a device for inputting data from outside the computer 600. The data I / F unit 605 is, for example, a drive device for reading data stored in various storage media. The data I / F unit 605 may be provided outside the computer 600. When the data I / F unit 605 is provided outside the computer 600, the data I / F unit 605 is connected to the computer 600 via an interface such as a USB.

[0112] The communication I / F unit 606 is a device for performing data communication via a network such as the Internet, either wired or wirelessly, with devices external to the computer 600. The communication I / F unit 606 may be provided outside the computer 600. When the communication I / F unit 606 is provided outside the computer 600, the communication I / F unit 606 is connected to the computer 600 via an interface such as a USB.

[0113] The display device 607 is a device for displaying various types of information. The display device 607 is, for example, a liquid crystal display, an organic EL (Electro-Luminescence) display, a display of a wearable device, or the like. The display device 607 may be provided outside the computer 600. When the display device 607 is provided outside the computer 600, the display device 607 is connected to the computer 600 via, for example, a display cable. Furthermore, when a touch panel is adopted as the input I / F unit 604, the display device 607 may be configured as an integral part of the input I / F unit 604.

[0114] The above describes one embodiment of the present invention. Information processing system 100 generates behavior change content by inputting obtainable first user information included in user information into a content generation model, evaluates the contribution of the first user information to the generation of the behavior change content based on a first contribution evaluation rule, and determines whether or not to acquire the first user information based on the contribution. This allows information processing system 100 to consider whether or not to acquire user information when generating behavior change content.

[0115] Furthermore, the information processing system 100 can acquire behavioral characteristic information and further input the behavioral characteristic information into the content generation model to generate behavior change content based on the user's behavioral characteristics. This allows the information processing system 100 to consider whether or not to acquire user information when generating behavior change content that takes the user's behavioral characteristics into account.

[0116] Furthermore, the information processing system 100 can evaluate the effectiveness of the post-input behavior change content based on the content evaluation rules, and evaluate the contribution of the first user information to the generation of the behavior change content in relation to the evaluated effectiveness. This allows the information processing system 100 to consider whether or not to acquire user information based on the effectiveness of the post-input behavior change content.

[0117] Furthermore, the information processing system 100 can further evaluate the effectiveness of the pre-input behavior change content based on the content evaluation rules, and evaluate the contribution of the first user information to the generation of the behavior change content based on the effectiveness of the pre-input behavior change content and the effectiveness of the post-input behavior change content. This allows the information processing system 100 to consider whether or not to acquire user information in terms of ROI, for example, based on the difference or disparity between the effectiveness of the post-input behavior change content and the pre-input behavior change content.

[0118] Furthermore, the information processing system 100 can evaluate the degree of contribution further based on the external environment information, thereby enabling the information processing system 100 to consider whether or not it is necessary to acquire user information based on the external environment information.

[0119] Furthermore, the information processing system 100 can generate a series of behavior change content and evaluate the effectiveness of a series of post-input behavior change content generated by inputting the first user information into the content generation model. This allows the information processing system 100 to consider whether or not to acquire user information when generating a series of behavior change content.

[0120] Furthermore, the information processing system 100 can perform an acquisition process to acquire first user information based on the result of the determination of necessity. Furthermore, the information processing system 100 can perform an acquisition process to not acquire first user information based on the result of the determination of necessity. This allows the information processing system 100 to acquire only first user information that is effective for generating behavior change content, for example.

[0121] Furthermore, the information processing system 100 can evaluate the contribution of each of the plurality of pieces of first user information and determine whether or not to acquire each of the plurality of pieces of first user information based on the contribution of each of the plurality of pieces of first user information. This allows the information processing system 100 to select only first user information that is effective in generating behavior modification content, for example.

[0122] It should be noted that the present embodiment is provided to facilitate understanding of the present invention and is not intended to limit the present invention. The present invention may be modified or improved without departing from the spirit thereof, and equivalents thereof are also included in the present invention.

[0123] In addition, in the present invention, a "unit" does not simply mean a physical means, but also includes cases where the functions of the "unit" are realized by software. Furthermore, the functions of one "unit" or device may be realized by two or more physical means, devices, or software, and the functions of two or more "units" or devices may be realized by one physical means, device, or software. [Explanation of symbols]

[0124] 100 Information processing system, 110 Storage unit, 120 Acquisition processing unit, 130 Update information acquisition unit, 140 Behavioral characteristic acquisition unit, 150 Content generation unit, 160 Content evaluation unit, 170 Contribution degree evaluation unit, 180 Acquisition necessity determination unit, 190 Content output unit, 195 Model update unit, 200 Information processing device

Claims

1. a content generation unit that inputs user information about a user into a content generation model that generates behavior change content for causing the user to perform a predetermined target behavior, and that inputs obtainable first user information included in the user information into the content generation model, thereby generating the behavior change content; a contribution evaluation unit that evaluates the contribution of the first user information to the generation of the behavior change content based on a contribution evaluation rule that evaluates the contribution of the first user information to the generation of the behavior change content; a content evaluation unit that evaluates the effectiveness of behavior change content in causing the user to perform a predetermined target behavior, and that evaluates the effectiveness of post-input behavior change content generated by inputting the first user information into the content generation model based on content evaluation rules; and an acquisition necessity determining unit that determines whether or not it is necessary to acquire the first user information based on the degree of contribution; Equipped with the contribution evaluation unit evaluates the contribution to the evaluated effect. Information management system.

2. A behavioral characteristic acquisition unit that acquires behavioral characteristic information related to the user's behavioral characteristics, the content generation model generates behavior change content based on the user information and the behavioral characteristic information; the content generation unit further inputs the behavioral characteristic information into the content generation model to generate the behavior change content based on the behavioral characteristic of the user. The information management system according to claim 1 .

3. the content evaluation unit further evaluates the effect of pre-input behavior change content generated without inputting the first user information into the content generation model based on the content evaluation rule; the contribution evaluation unit evaluates the contribution based on the effect of the pre-input behavior change content and the effect of the post-input behavior change content; The information management system according to claim 1 .

4. The information management system according to claim 1 , wherein the contribution evaluation unit evaluates the contribution based on external environment information relating to an external environment related to the execution of the predetermined target behavior.

5. the behavior change content includes a series of behavior change content corresponding to each of a plurality of behaviors to be performed until the predetermined target behavior is achieved; the content generation unit generates the series of behavior change content; the content evaluation unit evaluates the effect of a series of post-input behavior change contents generated by inputting the first user information into the content generation model; The information management system according to claim 1 .

6. The information management system according to claim 1 , further comprising an acquisition processing unit that performs an acquisition process to acquire the first user information based on a result of the determination of whether or not the first user information is necessary.

7. The information management system according to claim 6 , wherein the acquisition processing unit performs an acquisition process that determines not to acquire the first user information based on a result of the determination of whether or not the first user information is required.

8. the first user information includes a plurality of pieces of first user information; the contribution degree evaluation unit evaluates the contribution degree of each of the plurality of pieces of first user information based on the contribution degree evaluation rule; the acquisition necessity determining unit determines whether or not acquisition of each of the plurality of pieces of first user information is necessary based on the contribution degree of each of the plurality of pieces of first user information.

3. The information management system according to claim 1 or 2.

9. The computer inputting user information about a user into a content generation model that generates behavior change content for causing the user to perform a predetermined target behavior, and inputting obtainable first user information included in the user information into the content generation model, thereby generating the behavior change content; evaluating the contribution of the first user information to the generation of the behavior change content based on a contribution evaluation rule for evaluating the contribution of the first user information to the generation of the behavior change content; evaluating the effectiveness of behavior change content in inducing the user to perform a predetermined target behavior, based on content evaluation rules; and evaluating the effectiveness of post-input behavior change content generated by inputting the first user information into the content generation model. determining whether or not to acquire the first user information based on the degree of contribution; The evaluation of the degree of contribution is an evaluation of the degree of contribution to the evaluated effect. Information management method.

10. On the computer, inputting user information about a user into a content generation model that generates behavior change content for causing the user to perform a predetermined target behavior, and inputting obtainable first user information included in the user information into the content generation model, thereby generating the behavior change content; evaluating the contribution of the first user information to the generation of the behavior change content based on a contribution evaluation rule for evaluating the contribution of the first user information to the generation of the behavior change content; Evaluating the effectiveness of post-input behavior change content generated by inputting the first user information into the content generation model based on content evaluation rules that evaluate the effectiveness of the behavior change content in causing the user to perform a predetermined target behavior; determining whether or not it is necessary to acquire the first user information based on the degree of contribution; Execute The evaluation of the degree of contribution is an evaluation of the degree of contribution to the evaluated effect. program.

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