Information processing device, information processing method and program

Abstract

To provide information as to what degree a well-being value or a well-being index increases or decreases and conversely as to what a recommended behavior is on the basis of a desired well-being value or a desired well-being index, or the like.SOLUTION: In an information processing system, an information processing device 100 includes a reception part 10 for receiving user's attribute information inputted from operation parts 210 of a plurality of communicable user terminals 200, a first acquisition part 20 for acquiring a category different behavior in the user, a calculation part 55 for calculating a well-being value that increases or decreases by applying the category different behavior to an estimation model derived from the attribute information, and a second acquisition part 30 for acquiring a behavior value, wherein the calculation part 55 calculates the well-being value that increases or decreases by applying the category different behavior and a behavior value to the estimation model derived from the attribute information.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and a program that focus on the relationship between well-being and behavior. [Background technology]

[0002] Conventionally, a mode has been proposed that more effectively supports a subject's behavioral change by using a nudge based on a behavioral factor. For example, Patent Document 1 proposes a behavior support system that includes a storage unit that stores a plurality of messages for encouraging behavioral change in association with a plurality of behavioral factors, a prediction unit that predicts state information indicating the state of the subject for each of the plurality of behavioral factors based on subject information about the subject, a generation unit that selects one or more messages from the storage unit based on the state information and generates a message set including the one or more messages, and a control unit that controls output of the one or more messages in the message set to the subject. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-163957 A Summary of the Invention [Problem to be solved by the invention]

[0004] The present invention focuses on well-being, which is an indicator of happiness, goodness, satisfaction, etc., and provides an information processing device, information processing method, and program that can obtain information on how much a well-being value or well-being index will increase or decrease, or has increased or decreased, by selecting a certain behavior, and conversely, what behavior is recommended based on a desired well-being value or desired well-being index. [Means for solving the problem]

[0005] [Concept 1] The information processing device according to the present invention comprises: A reception unit that receives attribute information of a user; A first acquisition unit that acquires a category-specific behavior of the user; a calculation unit that calculates an increased or decreased well-being value or well-being index by applying the category-specific behavior to an estimation model derived from the attribute information; The present invention may also include:

[0006] [Concept 2] The information processing device according to concept 1 is A second acquisition unit for acquiring a behavior value, The calculation unit may calculate an increasing or decreasing well-being value or well-being index by applying the category-specific behavior and the action value to an estimation model derived from attribute information.

[0007] [Concept 3] In the information processing device according to concept 1 or 2, The calculation unit may calculate individual well-being indices by applying the category-specific behaviors to the estimation model, and calculate an overall well-being value based on the well-being indices.

[0008] [Concept 4] The information processing device according to the present invention comprises: A reception unit that receives attribute information of a subject; A selection unit that selects a category-specific behavior based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information; The present invention may also include:

[0009] [Concept 5] In the information processing device according to concept 4, The selection unit may select a category-specific behavior and an action value based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information.

[0010] [Concept 6] The information processing device according to concept 4 or 5 is The target attribute information relates to multiple subjects, The selection unit may select a category-specific behavior that maximizes a sum of well-being values ​​or well-being indexes for the multiple subjects.

[0011] [Concept 7] The information processing method according to the present invention comprises: A step of accepting attribute information of a user by a accepting unit; acquiring, by a first acquisition unit, a category-specific behavior of the user; A step of calculating, by a calculation unit, an increased or decreased well-being value or well-being index by applying the category-specific behavior to an estimation model derived from the attribute information; The present invention may also include:

[0012] [Concept 8] The information processing method according to the present invention comprises: A step of accepting attribute information of a subject by a accepting unit; selecting, by a selection unit, a category-specific behavior based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information; The present invention may also include:

[0013] [Concept 9] The program according to the present invention comprises: A program installed on a computer, The computer on which the program is installed A function for accepting user attribute information; A function of acquiring category-specific behavior of the user; A function of calculating an increased or decreased well-being value or well-being index by applying the categorical behavior to an estimation model derived from the attribute information; may be realized.

[0014] [Concept 10] The program according to the present invention comprises: A program installed on a computer, The computer on which the program is installed A reception function for receiving attribute information of a subject; A selection function for selecting a behavior by category based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information; may be realized. Effect of the Invention

[0015] According to the present invention, it is possible to obtain information as to how much a well-being value or well-being index will increase or decrease by selecting an action, or conversely, what action is recommended based on a desired well-being value or desired well-being index. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a schematic diagram for explaining an overview of an example of a processing mode in an information processing system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram of an information processing system used in the embodiment of the present invention. [Diagram 3] FIG. 3 is a diagram for explaining an example of an estimation model used in the embodiment (aspect 1) of the present invention. [Figure 4] FIG. 4 is a diagram for explaining an example of an estimation model used in the embodiment (aspect 2) of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] Embodiment "composition" Hereinafter, an embodiment of an information processing device according to the present invention will be described. In this embodiment, an information processing method using the information processing device, a program installed to generate the information processing device, and a storage medium such as a USB or DVD storing the program are also provided. In addition, a program installed in various terminals such as a personal computer, a smartphone, and a tablet is also provided. In this application, "or" is a concept including "and", and the term "A or B" means any one of "A", "B", and "A and B".

[0018] Typically, the information processing device 100 is capable of communicating with a plurality of user terminals 200. The user terminals 200 are terminals such as personal computers, smartphones, tablet terminals, wearable computers such as smart watches and smart glasses, and are typically mobile terminals such as smartphones and tablet terminals. The user terminals 200 may have an operation unit 210 that accepts operations from a user, and a display unit 220 that displays various information. In the case of smartphones and tablet terminals, since they are touch panels, the functions of both the operation unit 210 and the display unit 220 are performed on the display screen.

[0019] [Aspect 1] First, an aspect using an estimation model associated with attribute information will be described.

[0020] As shown in FIG. 2, the information processing device 100 may include a receiving unit 10 that receives attribute information of a user, which is an example of a subject, a first acquiring unit 20 that acquires categorized actions that are actions related to the user and are divided into a plurality of categories, a calculating unit 55 that calculates an increased or decreased well-being value by applying the categorized actions to an estimation model derived from the attribute information, and an output unit 80 that outputs the well-being value calculated by the calculating unit 55. Any information output by the output unit 80 may be displayed or notified by voice on the user terminal 200. When this aspect is adopted, information on how much the well-being value increases or decreases by the user selecting a certain action can be obtained. Therefore, before selecting a certain action, the user can select whether or not to perform the certain action. In addition, the categorized action may be input after performing a certain action, and in that case, the user can visually confirm how much the well-being value has increased or decreased by performing the certain action via the display unit 220. Note that the user terminal 200 may be configured to notify by voice how much the well-being value has increased or decreased, and in this case, the user can confirm the result by hearing.

[0021] The estimation model of this embodiment is typically a model for estimating an increase or decrease in the well-being value when a user belonging to a certain attribute performs a certain action. As an example, an estimation model in which the well-being value does not decrease but only increases may be used under the idea that taking a certain action always increases the well-being value. When user identification information such as a user ID is input from the operation unit 210, the user attribute information linked to the user identification information may be read from the storage unit 60 by the reception unit 10, and the attribute information may be received by the reception unit 10. In addition, the user attribute information may be input from the operation unit 210. Well-being means "a healthy and happy state. A good state. A satisfying state." The well-being value is a value related to such a state, and an increase in the well-being value means a happier, better, or more satisfying state.

[0022] The attribute information may include sex, age, marital status, activity level, occupation, annual income, family structure, place of employment, etc. The activity level may be determined by the determination unit 90 in consideration of hobbies, etc. input by the user. The determination unit 90 reads out the determination criteria stored in the storage unit 60, and may determine that the attribute is "very active" if the item corresponds to, for example, playing sports, music, etc., once a week for one hour or more, and may determine that the attribute is "not active" if the user does not have any particular hobby. The activity level may also be input as a self-report, and may be input by the user in five stages, such as "very active," "active," "average," "not very active," and "not active."

[0023] The categorized behavior may include the amount of behavior by category. In this case, the amount of behavior may be input as a number of times, such as once or twice, or when a certain categorized behavior is performed, the corresponding categorized behavior may be automatically counted. Categorical activities may include: (1a) eating at home, (2a) going out for meals or parties, (3a) dressing up (e.g., clothing, hairstyle, makeup), (4a) managing one's own or family's health or receiving medical treatment, (5a) going out to relax (e.g., taking a walk or taking a rest in the park), (6a) working, (7a) commuting to work or school, (8a) children's education or extracurricular activities, (9a) personal education, (10a) household chores such as cooking, cleaning, laundry, and shopping, (11a) shopping (for furniture, home appliances, hobbies, and entertainment), (12a) raising infants and small children, (13a) caring for family members, (14a) volunteering or local events, (15a) communicating with family, significant other, or acquaintances, (16a) sports, (17a) traveling or outings, (18a) hobbies or entertainment going out, and (19a) hobbies or entertainment at home. The category-specific behavior may be input by selecting an option from the user terminal 200 when the user performs any of the above (1a) to (19a), or the user may read a QR code (registered trademark) installed in a store or a terminal installed in the store with the user terminal 200, and the category-specific behavior of any of the above (1a) to (19a) may be automatically counted. Each of the behaviors 1 to 19 in FIG. 3 corresponds to the above (1a) to (19a), for example. The category-specific behavior may be linked to location information of the user terminal 200 such as a smartphone, a purchase history on the web, or the like. For example, when a user visits a certain store, the determination unit 90 may automatically determine that the user has eaten a meal depending on the time spent at the store. Also, for example, when a purchase is made on the web, the determination unit 90 may automatically input the category-specific behavior by linking it to the result of automatic shopping.

[0024] The calculation unit 55 may calculate individual well-being indices by applying category-specific actions (including category action amounts) to an estimation model derived from attribute information, and may calculate an overall well-being value based on the well-being indices. As an example, there may be a table in which category-specific actions and well-being indices are determined for each attribute (see FIG. 3), and it may be determined which well-being index increases or decreases when a certain category-specific action is input. In this embodiment, a plurality of tables associated with each attribute are stored in the storage unit 60. The attribute may be a category with a certain degree of width, and by adopting such an embodiment, the number of estimation models (for example, the table in FIG. 3) to be prepared can be suppressed to an appropriate range. In addition, the output unit 80 may output individual well-being indices that increase or decrease due to category-specific actions, and the well-being indices may be displayed on the display unit 220 or notified by voice.

[0025] For example, when action 1 is taken (see Figure 3), the values ​​of indicators 1 to 9 corresponding to action 1 are output, and the values ​​are simply added up, that is, f 1,1 +f 2,1 +···+f 9,1 In addition, a weight is set for each well-being index, and the sum of the well-being index and the weight (for example, when action 1 is performed, f 1,1 ×a 1,1 +f 2,1 ×a 2,1 +···+f 9,1 ×a 9,1 ) to calculate the well-being value. The well-being value may be output as an increment (see FIG. 1). When the amount of activity is m×n ("m" and "n" are integers), the well-being value may be m times that when the amount of activity is n. For example, when (5a) going out and relaxing the body and mind (walking, resting in the park, etc.) is performed four times a week, the well-being value may be four times that when (5a) going out and relaxing the body and mind (walking, resting in the park, etc.) is performed once a week.

[0026] Individual well-being indicators may include (1b) living a physically healthy life through appropriate exercise and diet, (2b) living a mentally healthy life without excessive stress, (3b) having income and assets necessary for living independently, (4b) having free time to use for oneself other than work, school, housework, and sleep, (5b) feeling connected to others such as family and friends and society through daily life, (6b) having mutual recognition with family, friends, superiors and colleagues at work, (7b) working toward realizing the person one wants to be through work, learning, hobbies, etc., (8b) feeling that one is useful to someone through work and social activities, and (9b) having expectations for life and society and hope for one's future. Indicators 1 to 9 in Figure 3 correspond to the above (1b) to (9b) as an example.

[0027] The individual well-being index or the overall well-being value serving as the basis may be linked to attribute information, and the individual well-being index or the overall well-being value serving as the basis linked to the attribute information may be returned to each time, and the attribute information and the category-specific behavior may be applied to the estimation model, so that the well-being index or the well-being value that increases or decreases with respect to the individual well-being index or the overall well-being value serving as the basis may be output (see FIG. 1). In this case, the base value before performing any behavior is determined based on the attributes of the user, and when performing any behavior, the increase or decrease with respect to the base value is output by the output unit 80. Alternatively, the individual well-being index or the overall well-being value for each user may be linked, and the well-being index or the well-being value may increase or decrease each time a category-specific behavior is input, and the accumulated amount of the well-being index or the well-being value linked to the user information may be output by the output unit 80. Even in this case, when a predetermined period has passed, the accumulated well-being index or the well-being value may be reset and returned to the base value determined based on the attributes of the user. As an example, a well-being index or well-being value associated with the behavior of the target user may be accumulated for one month, and when one month has passed, the well-being index or well-being value may be reset to the baseline value. Even in this case, the well-being index or well-being value linked to user information such as user identification information may be stored in the storage unit 60, and the history of the well-being index or well-being value may be checked upon request from the user.

[0028] The estimation model may be created in advance for each attribute to be classified, corresponding to each categorized behavior, by conducting a questionnaire or the like. In addition, a period for accumulating data may be set, and the estimation model may be generated using the accumulated data. Specifically, when a user performs a certain behavior during the period for accumulating data, any one of behaviors 1 to 19 or the amount of behavior may be input together with the attribute information of the user, and the well-being index for each of the indices 1 to 9 associated therewith may be input. Even if the user's attributes are input in detail, the estimation model may be linked to a superordinate conceptualization of the attribute. The average value of the accumulated data may be taken to generate an estimation model for determining the well-being index (e.g., indices 1 to 9 in FIG. 3) that increases or decreases depending on each behavior (e.g., behaviors 1 to 19 in FIG. 3) or the amount of behavior. As described above, when the amount of behavior is considered, when the amount of behavior is m×n times, it may be m times that when the amount of behavior is n times. Here, a value such as 1 to 5 may be selectively input for the well-being index. In the estimation model, the well-being value, which is an ordered value obtained from a questionnaire or the like, is used as the explained variable, and various attributes and behavioral information are used as explanatory variables, so ordered logit or ordered probit analysis may be used to estimate the order selection probability using the maximum likelihood method.

[0029] The information processing device 100 of this embodiment may have a selection unit 50 that receives attribute information of the subject at the reception unit 10, and selects a categorized behavior based on a desired well-being value in an estimation model that is linked to the attribute information and read out from the storage unit 60 by the reception unit 10. When such a mode is adopted, information on what behavior is recommended based on the desired well-being value can be obtained. The desired well-being value may be appropriately input from the operation unit 210, and a mode that "maximizes the well-being value" may be selected as described later, or as another example, a mode that "increases the well-being value by ●●" may be selected, or a mode that "minimizes the well-being value" may be selected. Note that, when the mode that "minimizes the well-being value" is selected, the user can understand which categorized behavior will cause the well-being value to increase the least or decrease the most, and can confirm measures that should not be taken. Note that the input item is the "well-being index" instead of the "well-being value", and the "desired well-being value" may be subdivided and input as the "desired well-being index".

[0030] The target attribute information is, for example, attribute information of subjects who are the subject of the survey. As an example, the selection unit 50 may select a category-specific behavior for maximizing an increasing well-being value or well-being index. The selection unit 50 may select a category-specific behavior or well-being index based on a total value of well-being values ​​for a plurality of subjects. As an example, the selection unit 50 may select a category-specific behavior that maximizes the total value of well-being values ​​or well-being indexes for a plurality of subjects. When such an embodiment is adopted, it is beneficial in that it is possible to grasp in advance what kind of behavior is preferable to emphasize when taking policies, measures, etc. for a plurality of subjects.

[0031] As an example, the information processing device 100 of the present embodiment may be used when creating a policy. For example, the output unit 80 may output what category-specific actions are required to increase the well-being value for residents of a certain area. In this case, residents (multiple users) residing in a certain area may be selected as subjects, and a request may be made from a user terminal 200 (e.g., a personal computer of a local government) to output category-specific actions that increase the well-being value, thereby outputting what actions should be prioritized among action 1, action 2, . . . , and action 19 (e.g., the above (1a) to (19a)). As an example of a processing method, the reception unit 10 may automatically read out attribute information of residents of a certain area from the storage unit 60, and the calculation unit 55 may automatically calculate well-being values ​​when action 1, action 2, . . . , and action 19 are performed in an estimation model corresponding to each attribute information of residents (multiple users) residing in a certain area, and the total of well-being values ​​(total of all residents) when any of action 1, action 2, . . . , and action 19 is performed may be automatically calculated. The selection unit 50 may then select the behavior that maximizes the well-being value from among behavior 1 to behavior 19. By adopting such an embodiment, it is possible to know which behavior, behavior 1, behavior 2, ..., behavior 19, will maximize the total well-being value for residents (multiple users) living in a certain area who have predetermined attribute information, and the user (e.g., a local government official) can infer whether it is beneficial to adopt a policy related to that behavior.

[0032] As another example, the information processing device 100 of the present embodiment may be used when inviting a new store to a shopping mall. For example, when considering inviting a new store targeting users with a certain attribute, the output unit 80 may output what category-specific behaviors are necessary to increase the well-being value. In this case, by inputting attribute information of the target user (e.g., 30-40 years old, "female", "married") and requesting the user terminal 200 to output category-specific behaviors that increase the well-being value, it may be possible to output what behavior should be prioritized among, for example, behavior 1, behavior 2, ..., behavior 19 (e.g., the above (1a) to (19a)). As an example of the processing method, in the estimation model corresponding to each of 30-year-old "female" and "married", 31-year-old "female" and "married", and 40-year-old "female" and "married", the calculation unit 55 may automatically calculate the well-being value when the behavior 1, the behavior 2, the behavior 19 are performed, and the total of the well-being value when any of the behaviors 1, the behavior 2, the behavior 19 are performed may be automatically calculated. Then, the selection unit 50 may select the behavior that maximizes the well-being value from the behaviors 1 to 19. By adopting such an embodiment, it is possible to grasp which of the behaviors 1, the behavior 2, the behavior 19 is performed to maximize the well-being value for multiple users aged 30 to 40 "female" and "married", and the user can infer whether it is beneficial to attract a store related to the behavior.

[0033] [Aspect 2] Next, an embodiment using an estimation model that also utilizes the action value will be described. Note that any embodiment described in embodiment 1 can also be adopted in embodiment 2. Conversely, any embodiment described in embodiment 2 can also be adopted in embodiment 1.

[0034] A second acquisition unit 30 that acquires an action value may be provided. The action value may include Wish (fulfillment of a wish), New (a new discovery), Great (value beyond expectations), Smooth (resolving a problem), and the like.

[0035] The user may input the action value via the user terminal 200. More specifically, when the action values ​​are divided into four categories, Wish (fulfillment of a wish), New (a new discovery), Great (value exceeding expectations), and Smooth (resolving a problem), the user may select one or more of these via the user terminal 200. Typically, one action value is selected.

[0036] When this aspect is adopted, the well-being value can be calculated using not only the categorized actions, which are actions or amounts of actions, but also the action value, which is the quality of the actions, which is beneficial in that a more appropriate well-being value can be calculated. In this case, the calculation unit 55 may calculate individual well-being indices by applying the categorized actions (including the categorized action amounts) and the action values ​​to the estimation model derived from the attribute information, and calculate the overall well-being value based on the well-being indices. As an example, there may be a table in which the categorized actions, action values, and well-being indices are determined for each attribute (see FIG. 4), and it may be determined which well-being indices increase or decrease when a certain categorized action and action value are input. When the action values ​​are taken into consideration and Wish (realization of a wish), New (new discovery), Great (value beyond expectations), and Smooth (resolving a problem) are used as action values, a simple calculation shows that four times as many estimation models are prepared as compared to the case in which the action values ​​are not taken into consideration (the above-mentioned "Aspect 1"). In addition, the calculation unit 55 may read out an estimation model including multiple action values ​​based on the attribute information, and then select an estimation model according to the action value, so that an estimation model derived from the attribute information and the action value is selected.

[0037] In this embodiment, the estimation model may be created in advance in correspondence with the categorized behavior for each attribute and behavior value by conducting a questionnaire or the like. In addition, in this embodiment, a period for accumulating data may be set, and the estimation model may be generated using the accumulated data. Specifically, when a user performs a certain behavior, the attribute information of the user may be input together with any one of the behaviors 1 to 19 or the amount of behavior, and any one of the behavior values ​​"Wish (realization of a wish)", "New (new discovery)", "Great (value beyond expectations)", and "Smooth (problem resolution)", and the well-being index for each of the indices 1 to 9 associated therewith may be input. Then, the average value of the accumulated data may be taken, and an estimation model may be generated for determining the well-being index (e.g., indices 1 to 9 in FIG. 4) that increases or decreases depending on each behavior (e.g., behaviors 1 to 19 in FIG. 4) or the amount of behavior (e.g., indices 1 to 9 in FIG. 4) for each behavior value (for each of "Wish (realization of a wish)", "New (new discovery)", "Great (value beyond expectations)", and "Smooth (problem resolution)"). In the estimation model, the well-being value, which is an ordered value obtained from a questionnaire or the like, is used as the explained variable, and various attributes and behavioral information are used as explanatory variables, so ordered logit or ordered probit analysis may be used to estimate the order selection probability using the maximum likelihood method.

[0038] The selection unit 50 may receive attribute information of the subject at the reception unit 10, and select a categorical behavior and an action value based on a desired well-being value in an estimation model linked to the attribute information and read from the storage unit 60 by the reception unit 10. When such an embodiment is adopted, information on what behavior and action value are recommended based on the desired well-being value can be obtained. In this embodiment, since the action value is also taken into consideration, in addition to what the recommended behavior is, information on the action value to be obtained by the behavior can be obtained, which is very useful in that the recommended behavior can be specified. Note that the input item is the "well-being index" instead of the "well-being value", and the "desired well-being value" may be subdivided and input as the "desired well-being index".

[0039] The target attribute information is, for example, attribute information of the subjects to be surveyed. As an example, the selection unit 50 may select a categorical behavior for maximizing the increasing well-being value or well-being index. The selection unit 50 may select a categorical behavior based on the total value of the well-being value or well-being index for multiple subjects. As an example, the selection unit 50 may select a categorical behavior that maximizes the total value of the well-being value or well-being index for multiple subjects. When adopting such an embodiment, it is beneficial in that when taking a policy or measure for multiple subjects, it is possible to grasp in advance what kind of behavior is preferable to emphasize while taking into account the action value, that is, the target action value.

[0040] As an example, the information processing device 100 of the present embodiment may be used when creating a policy. For example, the output unit 80 may output what combination of categorized actions and action values ​​will increase the well-being value for a certain local resident. In this case, by selecting certain local residents (multiple users) as subjects and requesting the output of combinations of categorized actions and action values ​​that will increase the well-being value from a user terminal 200 (e.g., a local government's personal computer), it may be output which action should be prioritized among, for example, action 1, action 2, ..., action 19 (e.g., the above (1a) to (19a)), and further output the action value that should be emphasized for that action. As an example of the processing method, the receiving unit 10 automatically reads out attribute information of residents of a certain area from the storage unit 60, and the calculation unit 55 automatically calculates well-being values ​​when categorized actions (action 1, action 2, ..., action 19) and action values ​​(action value 1, ..., action value 4) are combined in an estimation model corresponding to each attribute information of residents (multiple users) living in a certain area, and automatically calculates the total well-being value (total value for all residents) when any combination of categorized actions and action values ​​is performed. Then, the selection unit 50 may select a categorized action that maximizes the well-being value, and further output the action value that maximizes the well-being value for the selected action. By adopting such an embodiment, it is possible to know which of behaviors 1, 2, ..., and 19 will maximize the total well-being value for residents (multiple users) living in a certain area who have predetermined attribute information, and further to know the action value that should be emphasized for that action, allowing a user (e.g., a local government official) to infer whether it is beneficial to adopt a policy related to that action. Note that when selecting the category-specific actions and action values, it is also possible to adopt an embodiment in which the selection unit 50 selects the combination of category-specific actions and action values ​​that maximize the well-being value.

[0041] As another example, the information processing device 100 of the present embodiment may be used when inviting a new store to a shopping mall. For example, when considering inviting a new store to a target user with a certain attribute, the output unit 80 may output what combination of category-specific behavior and action value is required to increase the well-being value. In this case, by inputting attribute information of the target user (e.g., 30-40 years old, "female", "married") and requesting the user terminal 200 to output a combination of category-specific behavior and action value that increases the well-being value, it may be possible to output what behavior should be prioritized among, for example, behavior 1, behavior 2, ..., behavior 19 (e.g., the above (1a) to (19a)). Furthermore, it may be possible to output the action value that should be emphasized for that behavior. As an example of the processing method, in the estimation models corresponding to 30-year-old "female" and "married", 31-year-old "female" and "married", ..., and 40-year-old "female" and "married", the calculation unit 55 may automatically calculate the well-being value when a combination of categorized actions (action 1, action 2, ..., action 19) and action values ​​(action value 1, ..., action value 4) is performed, and the total of the well-being value when any combination of categorized actions and action values ​​is performed may be automatically calculated. Then, the selection unit 50 may select a categorized action from actions 1 to 19 that maximizes the well-being value, and further output the action value that maximizes the well-being value for the selected action. By adopting such an embodiment, it is possible to know which of the behaviors 1, 2, ..., and 19 will maximize the well-being value for multiple users who are 30 to 40 years old, "female," and "married," and further to know the action value that should be emphasized for that behavior, and the user can infer whether it is beneficial to invite a store related to that behavior. Note that, when selecting the category-specific behavior and action value, as described above, it is also possible to adopt an embodiment in which the selection unit 50 selects the combination of category-specific behavior and action value that maximizes the well-being value.

[0042] The above actions (1a) to (19a) and well-being indicators (1b) to (9b) are merely examples, and the content can be appropriately changed as necessary.

[0043] The above description of the embodiment and the disclosure of the drawings are merely examples for explaining the invention described in the claims, and the invention described in the claims is not limited by the above description of the embodiment or the disclosure of the drawings. In addition, the description of the claims at the time of filing is merely an example, and the description of the claims may be appropriately changed based on the description of the specification, drawings, etc. [Explanation of symbols]

[0044] 10 Reception 20 First Acquisition Department 30 Second Acquisition Department 50 Selection Department 60 Storage section 100 Information processing device

Claims

1. A reception unit that receives attribute information of a user; A first acquisition unit that acquires a category-specific behavior of the user; a calculation unit that calculates an increased or decreased well-being value or well-being index by applying the category-specific behavior to an estimation model derived from the attribute information; An information processing device comprising:

2. A second acquisition unit for acquiring a behavior value, The information processing device according to claim 1 , wherein the calculation unit calculates an increasing or decreasing well-being value or well-being index by applying the category-specific actions and the action values ​​to an estimation model derived from attribute information.

3. The information processing device according to claim 1 , wherein the calculation unit calculates an individual well-being index by applying the category-specific behavior to the estimation model, and calculates an overall well-being value based on the well-being index.

4. A reception unit that receives attribute information of a subject; A selection unit that selects a category-specific behavior based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information; An information processing device comprising:

5. The information processing device according to claim 4 , wherein the selection unit selects category-specific actions and action values ​​based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information.

6. The target attribute information relates to multiple subjects, The information processing device according to claim 4 , wherein the selection unit selects a category-specific behavior that maximizes a well-being value or a sum of well-being indices for the plurality of subjects.

7. A step of accepting attribute information of a user by a accepting unit; acquiring, by a first acquisition unit, a category-specific behavior of the user; A step of calculating, by a calculation unit, an increased or decreased well-being value or well-being index by applying the category-specific behavior to an estimation model derived from the attribute information; An information processing method comprising:

8. A step of accepting attribute information of a subject by a accepting unit; selecting, by a selection unit, a category-specific behavior based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information; An information processing method comprising:

9. A program installed on a computer, The computer on which the program is installed A function for accepting user attribute information; A function of acquiring category-specific behavior of the user; A function of calculating an increased or decreased well-being value or well-being index by applying the categorical behavior to an estimation model derived from the attribute information; A program to achieve this.

10. A program installed on a computer, The computer on which the program is installed A reception function for receiving attribute information of a subject; A selection function for selecting a behavior by category based on a desired well-being value or a desired well-being index in an estimation model derived from the attribute information; A program to achieve this.

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