Recommendation system, program for recommendation system, and information processing method

Abstract

To provide a recommendation system that can increase happiness of a user whose attribute information is similar to attributes pertaining to estimation models.SOLUTION: A recommendation system 100 comprises a user terminal 110 and a server 120. There are estimation models in which well-being values are priorly estimated based on attribute information of users and category-specific behavioral information. When a prescribed operation is performed at the user terminal, in the user terminal or server, recommendation means selects an estimation model for attribute information within a prescribed similarity range having a basis of attribute information of a user based on priorly entered attribute information of the user, narrows down destination information or service information with increased well-being values based on the estimation model of the attribute information within the prescribed similarity range having a basis of the attribute information of the user, and recommends it by displaying on a display unit 111 of the user terminal.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a recommendation system that includes a user terminal and a server and recommends a destination or a service to a user, a program thereof, and an information processing method.

Background Art

[0002] Conventionally, there is known a recommendation system that includes a user terminal and a server. When user's current situation information is input in the user terminal, a recommendation means having artificial intelligence in the user terminal or the server narrows down destination information in consideration of means-of-transportation information based on pre-input user preference information, the input user's current situation information, and the current location information of the user terminal, and also narrows down route information including means-of-transportation information, and displays and recommends, to a display unit of the user terminal, the narrowed-down route information and destination information as a set (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, since the above-described conventional recommendation system is configured to provide a user with a set of, for example, both destination information and route information that the user likes, the essential happiness of the user has not been sufficiently considered.

[0005] Therefore, the present invention solves the problems of the prior art as described above. That is, the object of the present invention is to provide a recommendation system, a program thereof, and an information processing method that can enhance the happiness of users with attribute information similar to the attributes related to the estimation model.

Means for Solving the Problems

[0006] The invention according to claim 1 is a recommendation system including a user terminal and a server for recommending a destination or service to a user. There is an estimation model that pre-estimates well-being values based on user attribute information and category-based behavior information. When a predetermined operation occurs in the user terminal, in the user terminal or the server, the recommendation means selects an estimation model of attribute information within a predetermined similarity range based on the pre-input user attribute information, narrows down destination information or service information with an increased well-being value based on the estimation model of attribute information within a predetermined similarity range based on the user's attribute information, and displays the narrowed-down destination information or service information on the display unit of the user terminal to make a recommendation. By this configuration, the above-described problems are solved.

[0007] In addition to the configuration of the recommendation system described in claim 1, the invention according to claim 2 is such that when it is determined that the destination of the recommendation has been reached based on the current location information of the user terminal, or when it is determined that the service application operation of the recommendation has been completed in the user terminal, the user terminal or the server calculates a well-being value correlated with satisfaction based on the category-based behavior information of the user by the recommendation, the user's attribute information, and the estimation model corresponding to the user's attribute information, and associates the attribute information with the destination information or service information and stores it in a database. By this configuration, the above-described problems are further solved.

[0008] The invention according to claim 3, in addition to the configuration of the recommendation system described in claim 2, when it is determined that the destination of the recommendation has been reached based on the current location information of the user terminal, or when it is determined that the service application operation of the recommendation has been completed on the user terminal, the evaluation items of satisfaction are displayed on the display unit of the user terminal, and when the action value information, which is the evaluation information of satisfaction, is input, the user terminal or the server calculates a well-being value correlated with the satisfaction based on the category-specific action information of the user by the recommendation, the input action value information, the attribute information of the user, and the estimation model corresponding to the attribute information of the user, and accumulates it in the database in association with the attribute information and the destination information or service information, thereby further solving the above-described problems.

[0009] The invention according to claim 4, in addition to the configuration of the recommendation system described in claim 2 or claim 3, the recommendation means displays, on the display unit of the user terminal, reason information related to the index items of the well-being value correlated with the satisfaction in addition to the destination information or service information, thereby further solving the above-described problems.

[0010] The invention according to claim 5, in addition to the configuration of the recommendation system described in claim 2 or claim 3, the user terminal or the server feeds back the well-being value according to the attribute information of the user accumulated in the database to the estimation model according to the attribute information, thereby further solving the above-described problems.

[0011] The invention according to claim 6, in addition to the configuration of the recommendation system described in claim 2 or claim 3, when the recommendation means narrows down the destination information or service information based on the estimation model of the attribute information within a predetermined similar range based on the attribute information of the user, the destination information or service information with a proven track record of increasing the well-being value is given priority over other destination information or service information, displayed on the display unit of the user terminal, and recommended, thereby further solving the above-described problems.

[0012] The invention according to claim 7 further solves the above-mentioned problems by, in addition to the configuration of the recommendation system described in claim 2 or claim 3, enabling the display unit of the user terminal to display on a map the destination information with a proven track record of increasing well-being values and displaying it in a form that changes according to the number of achievements with increased well-being values.

[0013] The invention according to claim 8 is a program for a recommendation system that includes a user terminal and a server and recommends a destination or service to a user, and includes: a predetermined operation presence / absence determination step for determining whether or not a predetermined operation has occurred in the user terminal; an estimated model selection step in which, when the predetermined operation has occurred, a recommendation means in the user terminal or the server selects an estimated model of attribute information within a predetermined similar range based on the pre-input user attribute information; a destination / service narrowing step within a similar range in which the recommendation means narrows down destination information or service information with increased well-being values based on the estimated model of attribute information within a predetermined similar range based on the user's attribute information; and a similar-attribute destination / service recommendation display step in which the user terminal displays the narrowed-down destination information or service information on the display unit of the user terminal to make a recommendation, thereby solving the above-mentioned problems.

[0014] The invention according to claim 9 is an information processing method for recommending a destination or service to a user, comprising: determining whether a predetermined operation has occurred on a user terminal; when the predetermined operation has occurred, in the user terminal or the server, a recommendation means selects an estimation model of attribute information within a predetermined similarity range based on the user's attribute information that has been input in advance; the recommendation means narrows down destination information or service information with an increased well-being value based on the estimation model of attribute information within a predetermined similarity range based on the user's attribute information; and the user terminal displays the narrowed-down destination information or service information on a display unit of the user terminal to make a recommendation, thereby solving the above-described problems.

Advantages of the Invention

[0015] The recommendation system of the present invention includes a user terminal and a server, and can not only communicate between the user terminal and the server to recommend a destination or service to the user, but also achieve the following specific effects.

[0016] According to the recommendation system of the invention according to claim 1, destination information or service information that is likely to increase the well-being value for a user with attribute information similar to the attributes related to the estimation model is recommended, so the happiness of a large number of users with attribute information similar to the attributes related to the estimation model can be enhanced. Furthermore, as the user's happiness increases, user utilization also increases, so the user's actions increase, leading to an increase in the monetary consumption for transportation means or at the destination or service, which can further promote the activation of the local economy and market. Also, since the destination area where the well-being value improves can be known, it is possible to check whether users who want to improve the well-being value have come to that area, and it is possible to provide advice on marketing to the businesses in that area.

[0017] According to the recommendation system of the invention according to claim 2, in addition to the effects achieved by the invention according to claim 1, since the well-being value is calculated after the action along the recommendation, the accuracy of the well-being value can be further improved, and the essential happiness of a large number of users with attribute information similar to the attributes related to the estimation model can be enhanced. Furthermore, since the attribute information with an increased well-being value and the destination information or service information are gradually accumulated in the database as a set, the accuracy of the recommendation of the destination information or service information that seems to be able to increase the well-being value according to the user's use can be improved.

[0018] According to the recommendation system of the invention according to claim 3, in addition to the effects achieved by the invention according to claim 2, since the well-being value is calculated after receiving the action value information, which is the evaluation information of satisfaction, after the action along the recommendation, the accuracy of the well-being value can be further improved, and the essential happiness of a large number of users with attribute information similar to the attributes related to the estimation model can be enhanced.

[0019] According to the recommendation system of the invention according to claim 4, in addition to the effects achieved by the invention according to claim 2 or claim 3, since the reason information of the recommendation is displayed on the display unit, the user can act after clearly understanding the purpose and reason for moving to the recommended destination or for receiving the recommended service. Furthermore, since the purpose and reason are understood and recognized, the essential happiness of the user can be further enhanced. In addition, since it is possible to know for what reason one has come to the area of the destination, it is possible to give advice on marketing to the businesses in that area.

[0020] According to the recommendation system of the invention according to claim 5, in addition to the effects achieved by the invention according to claim 2 or claim 3, since the information accumulated in the database is fed back to the estimation model, the accuracy of the recommendation that makes the user happy can be gradually improved.

[0021] According to the recommendation system of the invention according to claim 6, in addition to the effects achieved by the invention according to claim 2 or claim 3, destination information or service information with a proven track record of increased well-being value is recommended preferentially over other destination information or service information. Therefore, it is possible to further gradually increase the user's well-being value and enhance the user's essential happiness level. Furthermore, as the user's happiness level increases, their willingness to consume also increases. Therefore, it is possible to increase the monetary consumption in the recommended destination or service and further promote the activation of the local economy and market.

[0022] According to the recommendation system of the invention according to claim 7, in addition to the effects achieved by the invention according to claim 2 or claim 3, destination information is displayed on the map of the display unit of the user terminal in a form that changes according to the number of achievements with increased well-being value. Therefore, the user can understand the destination information with a proven track record at a glance, stimulate the user's willingness to act, and further promote the activation of the local economy. Furthermore, for the businesses in that area, since their characteristics are displayed in a visible form, it is possible to appeal to the users in a visible form about the characteristics of the businesses in that area. In addition, by also displaying item information about what kind of destination has an increased well-being value and item information about what kind of high satisfaction level there is, the user can easily know what kind of well-being value can be increased and what kind of satisfaction level can be increased by going to that destination. For example, it is possible to easily understand where the users who are seeking something come to frequently. Also, it is possible to easily understand that there are many users with a high satisfaction level for new discovery items at this destination.

[0023] According to the program of the recommendation system of the invention according to claim 8, similar to the effect achieved by the invention according to claim 1, destination information or service information that seems to be able to increase the well-being value for users with attribute information similar to the attributes related to the estimation model is recommended. Therefore, the happiness of a large number of users with attribute information similar to the attributes related to the estimation model can be increased. Furthermore, since an increase in user happiness leads to an increase in user utilization, the actions of users increase, resulting in an increase in monetary consumption for transportation means or at destinations or services, which can further promote the activation of the local economy and market. Also, since the destination area where the well-being value improves can be known, users who want to improve their well-being value can check whether they are coming to that area, and advice on marketing can be given to the businesses in that area.

[0024] According to the information processing method of the invention according to claim 9, similar to the effects achieved by the inventions according to claims 1 and 8, destination information or service information that seems to be able to increase the well-being value for users with attribute information similar to the attributes related to the estimation model is recommended. Therefore, the happiness of a large number of users with attribute information similar to the attributes related to the estimation model can be increased. Furthermore, since an increase in user happiness leads to an increase in user utilization, the actions of users increase, resulting in an increase in monetary consumption for transportation means or at destinations or services, which can further promote the activation of the local economy and market. Also, since the destination area where the well-being value improves can be known, users who want to improve their well-being value can check whether they are coming to that area, and advice on marketing can be given to the businesses in that area.

Brief Description of the Drawings

[0025]

Figure 1

Figure 2

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Figure 5

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Figure 8

Figure 9

Mode for Carrying Out the Invention

[0026] The recommendation system of the present invention includes a user terminal and a server, and has an estimation model that pre-estimates well-being values based on user attribute information and category-based behavior information. When a predetermined operation occurs on the user terminal, on the user terminal or the server, the recommendation means selects an estimation model of attribute information within a predetermined similarity range based on the pre-input user attribute information, and filters destination information or service information with an increased well-being value based on the estimation model of attribute information within a predetermined similarity range based on the user's attribute information, and displays the filtered destination information or service information on the display unit of the user terminal to make a recommendation. As long as it is possible to recommend destination information or service information to a large number of users with attribute information similar to the attributes related to the estimation model and increase the happiness of a large number of users with attribute information similar to the attributes related to the estimation model, the specific implementation mode can be any one. Also, the program of the recommendation system of the present invention includes a predetermined operation presence / absence determination step for determining whether a predetermined operation has occurred on the user terminal, and when a predetermined operation has occurred, on the user terminal or the server, the recommendation means selects an estimation model of attribute information within a predetermined similarity range based on the pre-input user attribute information (estimation model selection step), the recommendation means filters destination information or service information with an increased well-being value based on the estimation model of attribute information within a predetermined similarity range (similarity range destination / service filtering step), and the user terminal displays the filtered destination information or service information on the display unit of the user terminal to make a recommendation (similar attribute destination / service recommendation display step). As long as it is possible to recommend destination information or service information to a large number of users with attribute information similar to the attributes related to the estimation model and increase the happiness of a large number of users with attribute information similar to the attributes related to the estimation model, the specific implementation mode can be any one. Furthermore, the information processing method of the present invention includes a step of determining whether a predetermined operation has occurred on the user terminal, and when a predetermined operation has occurred, in the user terminal or the server, a recommendation means selects an estimation model of attribute information within a predetermined similarity range based on the user's attribute information that has been input in advance, a step in which the recommendation means narrows down destination information or service information with an increased well-being value based on the estimation model of attribute information within a predetermined similarity range based on the user's attribute information, and a step in which the user terminal displays the narrowed-down destination information or service information on the display unit of the user terminal and makes a recommendation. By having these steps, as long as it is possible to recommend destination information or service information to a large number of users with attribute information similar to the attributes related to the estimation model and increase the happiness of a large number of users with attribute information similar to the attributes related to the estimation model, the specific implementation mode can be any.

[0027] For example, the user terminal may be a notebook personal computer terminal, a smartphone terminal, a tablet terminal, a wristwatch-type terminal, a glasses-type terminal, etc., which has a display unit and an operation unit and transmits and receives information, and can be connected to the server by a communication network including a wide area network such as the so-called Internet, a local network, a telephone line, etc., and can be any as long as it can be connected to the server. Also, the server may be a cloud server created in a cloud environment, and the number of physical servers constituting the server may be one or more. Furthermore, the estimation model is typically a model for estimating the increase or decrease in the well-being value when a user belonging to a certain attribute performs a certain action. As an example, under the idea that the well-being value always increases when a certain action is taken, an estimation model that only increases without decreasing the well-being value may be used. Well-being refers to "a healthy and happy state. A good state. A satisfying state.", and the well-being value is a value related to such a state, meaning that a higher value indicates a state of happiness, goodness, or satisfaction. Furthermore, the attribute information may include gender, age, marital status (married or unmarried), activity level, occupation, annual income, family composition, workplace, etc. Regarding the activity level, it may be determined by considering information such as hobbies (such as schedule information) input from the user terminal and information obtained from the user terminal (such as information from a pedometer function).

Example

[0028] Hereinafter, the recommendation system 100 according to an embodiment of the present invention will be described with reference to FIGS. 1 to 9. Here, FIG. 1 is a diagram showing the concept of the recommendation system 100 according to an embodiment of the present invention, FIG. 2 is a chart diagram showing an operation example of the recommendation system 100 according to an embodiment of the present invention, FIG. 3 is a diagram showing an example of the my page screen 112 of the recommendation system 100 according to an embodiment of the present invention, FIG. 4 is a diagram showing an example of your mood screen 113 of the recommendation system 100 according to an embodiment of the present invention, FIG. 5 is a diagram for explaining an example of the estimation model EM of the first aspect used in the recommendation system 100 according to an embodiment of the present invention, FIG. 6 is a diagram showing an example of the recommendation screen 114 of the recommendation system 100 according to an embodiment of the present invention, FIG. 7 is a diagram for explaining an example of the estimation model EM of the second aspect used in the recommendation system 100 according to an embodiment of the present invention, FIG. 8 is a diagram showing an example of the satisfaction evaluation input window 115 of the recommendation system 100 according to an embodiment of the present invention, and FIG. 9 is a diagram showing an example of the search screen 116 of the recommendation system 100 according to an embodiment of the present invention.

[0029] As shown in FIG. 1, the recommendation system 100 according to an embodiment of the present invention includes a user terminal 110, a server 120, and a store terminal 130 which is an example of a product / service / location provider terminal. The user terminal 110 and the store terminal 130 are provided to be communicable with the server 120. And the recommendation system 100 has a database 121 of information such as the latest products, services, locations, etc. input from the store terminal 130 or the like, and is provided to recommend a destination or a service to the user.

[0030] The store terminal 130 uploads, for example, information on the products, services, and locations of the store to the server 120, or updates the information on the store's website, such as on a social networking service (hereinafter referred to as SNS). Also, the user logs in to the recommendation system 100 on the user terminal 110. And the user's attribute information AT and preference information LK are input in advance. Regarding the input of the attribute information AT, for example, on the "user registration" screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110, attribute information AT such as gender, age, married / unmarried status, activity level, occupation, annual income, family composition, workplace, etc. is input.

[0031] Also, regarding the method of inputting the preference information LK, for example, on the "things I like" screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110, there are categories such as gourmet, cafe, outdoor, shopping, going out, entertainment, fashion, indoor, etc., and a plurality of photos related to the category are displayed within each category. And the user selects one or more photos in which the things they like are shown. Tag information indicating the content shown in each photo is added. When a photo is selected by the user, the tag information of the selected photo is configured to be added as preference information LK, which is information on the things the user likes.

[0032] In addition to photos, it may be configured to select icons, keywords, voices, etc. Something is represented by the icon, keyword, and voice. In the case of voice, a button is displayed, and when the button is operated, something is output as voice. When the button is selected, the tag information of the content of the button is added as preference information LK. Also, the user may perform voice input about something they like using the microphone in the user terminal 110, or may perform text input about something they like in words or sentences using the input key, and configure it so that the information is added as preference information LK. Furthermore, on the "Your Personality" screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110, a plurality of simple questions are provided.

[0033] For example, questions such as "I like to meet people I've just met for the first time and can enjoy conversations with them even on the first meeting" are provided. And as an example, like a five - level evaluation, it is provided so that the user can intuitively answer each question with options such as "not at all applicable", "barely applicable", "neither applicable nor not applicable", "somewhat applicable", "completely applicable". When these answers are input by the user, in the user terminal 110 or the server 120, the recommendation means having artificial intelligence analyzes the answer information to obtain user type tendency information TP.

[0034] Furthermore, in this embodiment, there is an estimation model EM that pre - estimates the well - being value based on the user's attribute information AT and category - specific behavior information CA. Here, the estimation model EM may be created in advance corresponding to the category-specific behavior information CA for each classified attribute by conducting a questionnaire or the like. Also, a period for accumulating data may be provided, and the estimation model EM may be generated using the accumulated data. Specifically, during the period for accumulating data, when a user performs a certain action, along with the user's attribute information AT, any one of actions 1 to 19 or the action amount may be input, and the well-being index for each of indices 1 to 9 associated therewith may be input.

[0035] And suppose that the current situation information ST of the user is input as an example of a predetermined operation in the user terminal 110. Then, in the user terminal 110 or the server 120, the recommendation means selects an estimation model EM of the attribute information AT within a predetermined similar range based on the user's attribute information AT that has been input in advance. Note that an example of the predetermined operation is the input operation of the user's current situation information ST, but it is not limited to this. For example, it may be a search operation for destination information DN or service information. The predetermined operation may be any operation for the user to request the display of destination information DN or service information.

[0036] Then, the recommendation means narrows down the destination information DN with an increased well-being value based on the estimation model EM of the attribute information AT within a predetermined similar range based on the user's attribute information AT and the current location information of the user terminal 110 which is an example of an arbitrary element. Here, the narrowing down only needs to reduce a large number of information to a small number of information, and the small number may be one or more. At the same time, the recommendation means is configured to display the narrowed-down destination information DN on the display unit 111 of the user terminal 110 and make a recommendation. Note that although the destination information DN has been narrowed down, the service information with an increased well-being value may be narrowed down and recommended for display. In the estimation model EM, as an example, destination information DN and service information are associated with category-based action information CA.

[0037] In other words, assuming that user's current situation information ST is input as an example of a predetermined operation in the user terminal 110. Then, in the user terminal 110 or the server 120, the recommendation means narrows down the destination information DN and service information based on the pre-input user attribute information AT, the user's current situation information ST input as an example, and the current location information of the user terminal 110 which is an arbitrary element, and displays it on the display unit 111 of the user terminal 110 to make a recommendation.

[0038] Then, the user terminal 110 or the server 120 calculates a well-being value based on the user's category-based action information CA along the recommendation, associates it with the destination information DN, service information, and attribute information AT, and accumulates it in the database 121. This accumulated data may become the estimation model EM. Subsequently, when other user's current situation information ST is input as an example of a predetermined operation in another user terminal 110, the recommendation means, based on the pre-input attribute information AT of the other user and the current location information of the other user terminal 110 which is an arbitrary element, narrows down the destination information DN and service information that increase the well-being value of users with attribute information AT within a predetermined similar range based on the attribute information AT of the other user, and is configured to display it on the display unit 111 of the other user terminal 110 to make a recommendation.

[0039] As a result, destination information DN or service information that seems likely to increase the well-being value for users with attribute information AT similar to the attributes related to the estimation model EM is recommended. As a result, the happiness of a large number of users with attribute information AT similar to the attributes related to the estimation model EM can be enhanced. Furthermore, as user satisfaction increases, user utilization also increases. As a result, user actions increase, leading to increased monetary consumption on transportation means, at destinations, or for services, which can further promote the activation of the local economy and market. Also, it becomes possible to identify destination areas where the well-being value is improving. As a result, it is possible to check whether users who want to improve their well-being value are coming to that area. And it is possible to provide advice on marketing to the businesses in that area.

[0040] Subsequently, the operation example (information processing method) of the recommendation system 100 will be described in detail. As shown in FIG. 2, in step S1, as an attribute and preference information input determination step, it is determined whether the user's attribute information AT and preference information LK are input in the user terminal 110. If it is determined that the user's attribute information AT and preference information LK have been input, the process proceeds to step S2. On the other hand, if it is determined that they have not been input yet, step S1 is repeated.

[0041] In step S2, as an attribute and preference information registration step, the input attribute information AT and preference information LK are registered on the application of the recommendation system 100. More specifically, the attribute information AT and preference information LK input in the user terminal 110 are sent from the user terminal 110 to the server 120, and the server 120 associates the received attribute information AT and preference information LK with the user identification information and registers them in the database 121.

[0042] As shown in FIG. 3, when the user's attribute information AT and preference information LK are registered, the user's attribute information AT and preference information LK are displayed on the my page screen 112 of the recommendation system 100 shown on the display unit 111 of the user terminal 110. More specifically, the tag information of the photo selected by the user is registered as the preference information LK, and these tag information are configured to be displayed in the item of "Things and Activities I Like".

[0043] Note that the recommendation means may be configured to display the user type tendency information TP obtained based on the response information answered on the "Your Personality" screen (not shown) described above in the item of "Your Personality" on the my page screen 112. As an example, the user type tendency information TP has items such as openness, honesty, extroversion, cooperativeness, and neurotic tendency, and is configured to be displayed by the level values in each item. These user type tendency information TP are configured to be registered in the database 121 in the server 120, similar to the user's preference information LK.

[0044] In step S3, as a determination step of the presence or absence of a predetermined operation, the user terminal 110 or the server 120 determines whether the current situation information ST of the user has been input as an example of a predetermined operation on the user terminal 110. Note that as described above, the predetermined operation may be a search operation. For example, as shown in FIG. 4, on the "Your Mood" screen 113 of the recommendation system 100 shown on the display unit 111 of the user terminal 110, the current situation information ST of the user is provided so that it can be input.

[0045] On the "Your Mood" screen 113, input items are provided for information about the people together, free time information, appetite and material desire information, and active and rest desire information. Regarding the item of information about the people together, as an example, options such as alone, couple, friends, family, etc. are set so that it can be known whether the user is alone or with whom. Furthermore, regarding the item of free time information, it is provided so that the current amount of free time can be freely input.

[0046] In addition, for the items of appetite and material desire information, it is provided so that the user can freely input which one has a greater weight. Furthermore, for the items of active and rest desire information, it is provided so that the user can freely input which one has a greater weight. When there is an input for at least one of these, if the current situation information ST of the user is input, the user terminal 110 or the server 120 makes a determination. If it is determined that there is an input, proceed to step S4; on the other hand, if it is determined that there is not yet an input, repeat step S3.

[0047] Note that as the current situation information ST of the user, items for inputting information on the current presence or absence of automobile use, the presence or absence of motorcycle use, the user's luggage information, the user's fatigue level information, the moving step count information, and the calorie intake information may be provided. Furthermore, as the current situation information ST of the user, not only what the user inputs but also the current location information, date and time information, weather and temperature information, electronic payment information such as IC cards and electronic money, etc. may be automatically input.

[0048] Basically, within the free time, move from the current location to the destination, have some experience at the destination, and then move back from the destination to the current location. However, in order to handle the case where the user does not return to the current location, an item for inputting the user's final destination information may be provided. For example, it is used when the final destination is determined and the user wants to go to the final destination via a certain destination during the free time. Regarding the input method, the camera of the user terminal 110 may be used to photograph the user's facial expression, and the fatigue level information may be estimated and input using image analysis.

[0049] Also, the moving step count information may be input using the walking history information of the step counter function of the user terminal 110, and the fatigue level information may be estimated. Furthermore, based on the position information of the user terminal 110, the moving distance may be estimated, the calorie consumption information may be estimated, and the fatigue level information may be estimated. Alternatively, the camera of the user terminal 110 may be used to photograph the intake such as meals, and the calorie intake information may be estimated using image analysis. Furthermore, a smartwatch terminal, which is a wristwatch-type terminal worn on the user's wrist, may be used to input the user's body temperature information, heart rate information, moving distance information, moving step count information, etc.

[0050] Also, the camera may be used to photograph the user's luggage, and the luggage information may be estimated and input using image analysis. Furthermore, the camera may be used to photograph a car or a motorcycle, and the information on the current presence or absence of car use or motorcycle use may be estimated and input using image analysis. Also, the input is not limited to being by the user's operation. For example, it may be configured to be automatically input at all times, or it may be configured to be automatically input when the application of the recommendation system 100 is launched.

[0051] In step S4, as the estimation model selection step, in the user terminal 110 or the server 120, the recommendation means selects an estimation model EM of the attribute information AT within a predetermined similarity range based on the user's attribute information AT that has been input in advance. As the predetermined similarity range, for example, when the user's attribute information AT is female, 26 years old, single, and activity level 5, as an example, an estimation model EM of the attribute information AT of female, 25 - 29 years old, single, and activity level 4 - 6 is selected.

[0052] As shown in FIG. 5, the estimation model EM has a table in which category-specific action information CA and well-being indicators are determined for each attribute. The category-specific action information CA is the categories of actions 1 to 19 of "increase in action" in FIG. 5. And, as an example, Actions 1 to 19 correspond to (1a) having meals at home, (2a) going out for meals / banquets, (3a) being fashionable (clothing / hair style, makeup, etc.), (4a) health management / diagnosis of oneself and family members, (5a) going out to relax physically and mentally (taking a walk / resting in a park, etc.), (6a) working, (7a) commuting to work / school, (8a) children's learning / extracurricular activities, (9a) one's own learning, (10a) housework such as cooking, cleaning, washing, shopping, etc., (11a) shopping (furniture / home appliances, hobbies, entertainment-related), (12a) raising infants, (13a) nursing family members, (14a) volunteering / community events, (15a) communication with family members, lovers, acquaintances, (16a) sports, (17a) traveling / pleasure trips, (18a) hobbies / entertainment when going out, (19a) hobbies / entertainment at home, etc., of (1a) to (19a).

[0053] Regarding the action information CA by category, it may be linked to the location information of the user terminal 110 such as a smartphone or the purchase history on the web, etc. For example, when going to a certain store, it may be automatically determined that a meal has been had according to the staying time at this store. Also, for example, when purchasing on the web, it may be linked to the result of automatically conducting shopping so that the action information CA by category is automatically input.

[0054] Regarding the calculation of the well-being value, by applying the action by category (including the action amount by category) to the estimation model EM derived from the attribute information AT, an individual well-being index may be calculated, and the overall well-being value may be calculated based on this well-being index. As an example, there may be a table in which the action information CA by category and the well-being index are determined for each attribute, and it may be determined which well-being index increases or decreases when a certain action information CA by category is input. For example, when Action 1 is performed (see Fig. 5), the values of Indexes 1 to 9 corresponding to Action 1 are output, and these values are simply added together, that is, simply f 1,1 +f 2,1 +···+f 9,1It may be calculated so that a well-being value is calculated.

[0055] Also, a weight is determined for each well-being indicator, and the total value obtained by summing the well-being indicator × 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 ) may be used to calculate the well-being value. The well-being value may be output as an increment. When the amount of action is m × n (where "m" and "n" are integers), it may be made m times that when the amount of action is n times. For example, when going out (5 a) and relaxing physically and mentally (such as taking a walk and resting in the park) 4 times a week, it may be 4 times that when going out (5 a) and relaxing physically and mentally (such as taking a walk and resting in the park) 1 time a week.

[0056] The well-being indicators are, as an example, composed of individual well-being indicators, indicator 1 to indicator 9. Indicators 1 to 9 (individual well-being indicators) are, as an example, (1 b) being able to lead a physically healthy life through appropriate exercise and diet, (2 b) having no excessive stress and being able to lead a mentally healthy life, (3 b) having income and assets necessary for self-sufficiency in life, (4 b) ensuring free time for oneself other than work, school, housework, and sleep, (5 b) feeling a connection with others such as family and friends and society through daily life, (6 b) mutually approving with family, friends, superiors and colleagues at work, (7 b) being able to work towards realizing the self one wants to be through work, study, hobbies, etc., (8 b) feeling that one is useful to someone through work and social activities, (9 b) having expectations for life and society and having hope for one's future, corresponding to (1 b) to (9 b). As described above, in the estimation model EM, for example, destination information DN and service information are associated with category-based action information CA.

[0057] In step S5, as a similar-range destination / service narrowing-down step, the recommendation means, for example, based on the current situation information ST of the input user, the current location information of the user terminal 110 which is an arbitrary element, and the estimation model EM of the attribute information AT within a predetermined similar range based on the user's attribute information AT, narrows down the destination information DN or service information whose well-being value has been increased.

[0058] In step S6, as a similar-attribute destination / service recommendation display step, the user terminal 110 displays the narrowed-down destination information DN or service information on the display unit 111 of the user terminal 110 to make a recommendation. More specifically, as shown in FIG. 6, for example, the display unit 111 of the user terminal 110 displays a recommendation screen 114. On the recommendation screen 114, for example, map information including the current location of the user terminal 110, icons IC of one or more narrowed-down destination information DN, and route information RT from the current location to one or more destinations are displayed.

[0059] For example, assume that the user's attribute information AT is 26 years old, female, single, with an activity level of 5 and likes parks. In this case, as an example of the estimation model EM of the attribute information AT within a predetermined similar range based on this user's attribute information AT, an estimation model EM of the attribute information AT of female, 25 - 29 years old, single, with an activity level of 4 - 6 is selected. Then, based on the selected estimation model EM, the destination information DN whose well-being value has been increased is narrowed down. Subsequently, as an example of the narrowed-down destination information DN, a park where plants can be slowly admired is recommended.

[0060] Assume that the attribute information AT of the other party, the user, is 41 years old, female, married, has children, and has an activity level of 5 and likes parks. In this case, as an example of the estimation model EM of the attribute information AT within a predetermined similar range based on the attribute information AT of this user, an estimation model EM of the attribute information AT of female, 40 - 44 years old, married, having children, and with an activity level of 4 - 6 is selected. Then, based on the selected estimation model EM, narrow down the destination information DN with an increased well - being value. Subsequently, as an example of the narrowed - down destination information DN, recommend a park where the family can exercise. Note that on the recommendation screen 114, although the icon IC of the destination information DN is displayed on the map, it is not limited to this format. The recommended destination information DN and service information may be displayed in a list format.

[0061] In other words, regarding the configuration of the above steps, the program of the recommendation system 100, as a step for determining the presence or absence of a predetermined operation, determines whether the current situation information ST of the user is input as an example of a predetermined operation on the user terminal 110. Next, as a destination / service narrowing - down step, on the user terminal 110 or the server 120, the recommendation means narrows down the destination information DN and service information based on the pre - input attribute information AT of the user, the currently input situation information ST of the user as an example, and the current location information of the user terminal 110 which is an arbitrary element.

[0062] Subsequently, as a destination / service recommendation display step, the user terminal 110 displays the narrowed - down destination information DN or service information on the display unit 111 of the user terminal 110 to make a recommendation. Furthermore, as a well-being value calculation and accumulation step, the user terminal 110 or the server 120 calculates a well-being value based on the category-specific action information CA of the user along the recommendation, and accumulates it in the database 121 in association with the destination information DN or the service information and the attribute information AT. This accumulated data may become the estimation model EM.

[0063] Also, as a step S3 for determining the presence or absence of a predetermined operation of another user, it is determined whether or not the current situation information ST of another user is input as an example of a predetermined operation in another user terminal 110. Subsequently, as a similar range destination / service narrowing step S5 (including S4), in the other user terminal 110 or the server 120, the recommendation means, based on the attribute information AT of another user input in advance and the current location information of the other user terminal 110 which is an arbitrary element, narrows down the destination information DN or the service information that increases the well-being value of the users with the attribute information AT within a predetermined similar range based on the attribute information AT of another user. Then, as a similar attribute destination / service recommendation display step S6, the other user terminal 110 displays the narrowed-down destination information DN or service information on the display unit 111 of the other user terminal 110 to make a recommendation.

[0064] As a result, as described above, the destination information DN or the service information that seems to be able to increase the well-being value for the users with the attribute information AT similar to the attributes related to the estimation model EM is recommended. As a result, the happiness of a large number of users with the attribute information AT similar to the attributes related to the estimation model EM can be enhanced. Furthermore, as the user's happiness increases, user utilization also increases. As a result, the user's actions increase, leading to an increase in the monetary consumption for the means of transportation or at the destination or service, which can further promote the activation of the local economy and the market. Also, it becomes possible to know the destination area where the well-being value improves. As a result, it is possible to check whether a user who wants to improve the well-being value has come to that area. And it is possible to give advice on marketing to the businesses in that area.

[0065] Furthermore, in this embodiment, when destination information DN is recommended, it is assumed that it is determined that the recommended destination has been reached based on the current location information of the user terminal 110. Then, at this time, the user terminal 110 or the server 120 calculates a well-being value correlated with satisfaction based on the category-based action information CA of the user by the recommendation, the attribute information AT of the user, and the estimation model EM corresponding to the attribute information AT of the user. And it is configured to accumulate the calculated well-being value in the database 121 in association with the attribute information AT and the destination information DN. The method of calculating the well-being value is as described above. In addition, in the case where service information is recommended, for example, when the settlement operation for the recommended service information is completed in the user terminal 110, it is determined that the service application operation is completed based on, for example, the http response. Then, a well-being value is calculated in the same manner as when the destination information DN is recommended. And it is configured to accumulate the calculated well-being value in the database 121 in association with the attribute information AT and the service information.

[0066] Thereby, the well-being value is calculated after the action according to the recommendation. As a result, the accuracy of the well-being value can be further improved, and the essential happiness of a large number of users with attribute information AT similar to the attributes related to the estimation model EM can be enhanced. Furthermore, the attribute information AT with an increased well-being value and the destination information DN or the service information are gradually accumulated in the database 121 as a set. As a result, it is possible to improve the accuracy of recommendations for destination information DN or service information that can likely increase well-being values according to user usage.

[0067] Also, in this embodiment, as shown in FIG. 7, the estimation model EM of the second aspect may be used. In the estimation model EM of the second aspect, in addition to the elements of the estimation model EM of the first aspect shown in FIG. 5, elements of action value information, which is satisfaction evaluation information SF, are added. As an example, the action value information is composed of action values 1 to 4, which are individual action value information. As an example, action values 1 to 4 correspond to (1 c) to (4 c) of "(1 c) 'Wish (realization of a wish)', (2 c) 'New (new discovery)', (3 c) 'Great (value beyond expectation)', (4 c)'Smooth (resolution of troubles)'.

[0068] Then, as shown in FIG. 8, when destination information DN is recommended, when it is determined that the recommended destination has been reached based on the current location information of the user terminal 110, a satisfaction evaluation input window 115 is displayed on the display unit 111 of the user terminal 110. On the satisfaction evaluation input window 115, buttons corresponding to (1 c) 'Wish (realization of a wish)', (2 c) 'New (new discovery)', (3 c) 'Great (value beyond expectation)', and (4 c)'Smooth (resolution of troubles)', which correspond to action values 1 to 4, are displayed as satisfaction evaluation items for the satisfaction evaluation information SF.

[0069] And it is assumed that action value information, which is satisfaction evaluation information SF, is input. Then, the user terminal 110 or the server 120 calculates a well-being value correlated with satisfaction based on the user's category-based action information CA by recommendation, the input action value information, the user's attribute information AT, and the estimation model EM corresponding to the user's attribute information AT. Regarding the calculation of specific well-being values, for example, when Action 1 is performed and the action value 1 (Wish (fulfillment of a desire)) is evaluated (see Fig. 7), the values of indicators 1 to 9 corresponding to Action 1 when the action value 1 (Wish (fulfillment of a desire)) is evaluated are output, and these values are simply added together, that is, simply f 1,1,1 +f 2,1,1 +···+f 9,1,1 may be calculated so that the well-being value is calculated. And it is configured to store the calculated well-being value in the database 121. Regarding the case where service information is recommended, when the settlement operation for the recommended service information is completed on the user terminal 110, for example, based on the http response, it is determined that the service application operation is completed. Then, similar to the case where the destination information DN is recommended, a satisfaction evaluation input window 115 is displayed on the display unit 111 of the user terminal 110. And when the action value information, which is the satisfaction evaluation information SF, is input, a well-being value is calculated in the same manner as when the destination information DN is recommended. And it is configured to store the calculated well-being value in the database 121 in association with the attribute information AT and the service information.

[0070] As a result, the well-being value is calculated after receiving the input of the action value information, which is the satisfaction evaluation information SF, following the recommendation. As a result, the accuracy of the well-being value can be further improved, and the essential happiness of a large number of users with attribute information AT similar to the attributes related to the estimation model EM can be enhanced.

[0071] In the recommendation screen 114 of FIG. 6, although the map information including the current location, the icons IC of one or more filtered destination information DN, and the route information RT from the current location to one or more destinations are displayed, in addition to these, reason information related to the index items of the well-being value correlated with the satisfaction level may be configured to be displayed on the display unit 111 of the user terminal 110. Similarly, when the recommended service information is displayed in a list format on the recommendation screen 114, reason information related to the index items of the well-being value correlated with the satisfaction level may be added and displayed. More specifically, the specific contents of (1b) to (9b) of the above-described indicators 1 to 9 (individual well-being indicators) are concisely displayed.

[0072] As a result, the reason information for the recommendation is displayed on the display unit 111. As a result, the user can act after clearly understanding the purpose and reason for moving to the recommended destination or for receiving the recommended service. Furthermore, the user understands and becomes conscious of the purpose and reason. As a result, the essential happiness level of the user can be further increased. Also, it becomes clear for what reason the user has come to the area of the destination. As a result, advice can be given regarding marketing to the businesses in that area.

[0073] Furthermore, in the present embodiment, the user terminal 110 or the server 120 is configured to feedback the well-being values for each user attribute information AT stored in the database 121 to the estimation model EM for each attribute information AT. As a result, the information stored in the database 121 is fed back to the estimation model EM. As a result, the accuracy of the recommendation for making the user happy can be gradually improved. That is, the destination information DN and the service information are also fed back in association with the well-being value. As a result, the accuracy of the recommended destination information DN and service information can be gradually improved.

[0074] Also, in this embodiment, as described above, the recommendation means narrows down the destination information DN based on the estimation model EM of the attribute information AT within a predetermined similar range based on the user's attribute information AT. At this time, the destination information DN or service information with a proven track record of increasing the well-being value is handled preferentially over other destination information DN or service information. And the destination information DN or service information with a proven track record of increasing the well-being value is configured to be preferentially displayed on the display unit 111 of the user terminal 110 for recommendation over other destination information DN or service information.

[0075] As a result, the destination information DN or service information with a proven track record of increasing the well-being value is recommended preferentially over other destination information DN or service information. As a result, the well-being value of the user can be further gradually increased, and the essential happiness of the user can be enhanced. Furthermore, when the user's happiness level increases, the willingness to consume also increases. As a result, it is possible to increase the monetary consumption in the recommended destination or service and further promote the activation of the regional economy and market.

[0076] Furthermore, in this embodiment, as shown in FIG. 9, a search screen 116 is displayed on the display unit 111 of the user terminal 110 by a search operation, and the destination information DN with a proven track record of increasing the well-being value can be freely displayed on the map. At the same time, the destination information DN is configured to be displayed in a form that changes according to the number of proven results of the increased well-being value. As an example, in the estimation model EM of the attribute information AT within a predetermined similar range based on the user's attribute information AT, the destination information DN with a proven track record of increasing the well-being value is displayed on the map. At this time, the size of the icon IC of the destination information DN is enlarged and displayed according to the number of achievements with increased well-being values. Also, according to the action value information and the types of individual well-being indicators, the colors of the icon ICs of the destination information DN may be color-coded and displayed.

[0077] As a result, the destination information DN is displayed in a form that changes according to the number of achievements with increased well-being values on the map of the display unit 111 of the user terminal 110. As a result, the user can understand the proven destination information DN at a glance, stimulate the user's motivation to act, and further promote the activation of the local economy. Furthermore, for the businesses in that area, their characteristics are displayed in a visible form. As a result, the characteristics of the businesses in that area can be appealed to the user in a visible form.

[0078] In addition, by also displaying the item information on what kind of destination has an increased well-being value and the item information on what kind of high satisfaction level, the user can easily know what kind of well-being value can be increased and what kind of satisfaction level can be increased by going to that destination. For example, it can be easily understood where users who are seeking something come to frequently. Also, it can be easily understood that there are many users with a high satisfaction level for new discovery items at this destination.

[0079] The recommendation system 100, which is an embodiment of the present invention obtained in this way, includes a user terminal 110 and a server 120, and there is an estimation model EM that pre-estimates well-being values based on user attribute information AT and category-based behavior information CA. When current situation information ST of the user is input at the user terminal 110 as an example of a predetermined operation, at the user terminal 110 or the server 120, the recommendation means selects an estimation model EM of attribute information AT within a predetermined similarity range based on the pre-input user attribute information AT, and narrows down destination information DN or service information with the well-being value increased based on the estimation model EM of attribute information AT within a predetermined similarity range based on the user attribute information AT, and displays the narrowed-down destination information DN or service information on the display unit 111 of the user terminal 110 to make a recommendation. By doing so, it is possible to increase the happiness of a large number of users with attribute information AT similar to the attributes related to the estimation model EM, increase the user's actions and the monetary consumption in the means of transportation or at the destination or service, and further promote the activation of the regional economy and market. It is possible to confirm whether a user who wants to improve the well-being value has come to that area, and it is possible to give advice on marketing to the businesses in that area.

[0080] Furthermore, when it is determined that the recommended destination has been reached based on the current location information of the user terminal 110, or when it is determined that the service application operation for the recommendation has been completed on the user terminal 110, the user terminal 110 or the server 120 calculates a well-being value correlated with satisfaction based on the category-specific action information CA of the user by the recommendation, the attribute information AT of the user, and the estimation model EM corresponding to the attribute information AT of the user, and associates it with the attribute information AT and the destination information DN or service information and accumulates it in the database 121. By doing so, it is possible to increase the essential happiness of a large number of users with attribute information AT similar to the attributes related to the estimation model EM, and it is possible to improve the accuracy of the recommendation of the destination information DN or service information that can increase the well-being value according to the user's use.

[0081] Also, when it is determined that the recommended destination has been reached based on the current location information of the user terminal 110, or when it is determined that the service application operation for the recommendation has been completed on the user terminal 110, the display unit 111 of the user terminal 110 displays the evaluation items of satisfaction. When the action value information, which is the evaluation information SF of satisfaction, is input, the user terminal 110 or the server 120 calculates a well-being value correlated with satisfaction based on the category-specific action information CA of the user by the recommendation, the input action value information, the attribute information AT of the user, and the estimation model EM corresponding to the attribute information AT of the user, and associates it with the attribute information AT and the destination information DN or service information and accumulates it in the database 121. By doing so, the accuracy of the well-being value can be further increased, and the essential happiness of a large number of users with attribute information AT similar to the attributes related to the estimation model EM can be increased.

[0082] Furthermore, the index items of well-being values correlated with satisfaction include, for example, being able to lead a physically healthy life through exercise and diet, being able to lead a mentally healthy life without excessive stress, having income and assets necessary for self-sufficiency in life, ensuring time that can be freely used by oneself outside of work, school, housework, and sleep, feeling connected with family, others, and society through daily life, mutually approving with family, friends, superiors, and colleagues at work, being able to work towards realizing oneself as one wants through work, learning, and hobbies, having a sense of contributing to someone through work and social activities, having expectations for life and society and having hope for one's own future. The recommendation means, in addition to the destination information DN or service information, is configured to display reason information related to the index items of well-being values correlated with satisfaction on the display unit 111 of the user terminal 110. As a result, the user can act after clearly understanding the purpose and reason for moving to the recommended destination or for receiving the recommended service, can enhance the user's essential happiness more, and can give advice on marketing to the businesses in that area.

[0083] Also, by configuring the user terminal 110 or the server 120 to feedback the well-being values of the user accumulated in the database 121 for each user attribute information AT to the estimation model EM for each attribute information AT, the accuracy of the recommendation for making the user happy can be gradually improved.

[0084] Furthermore, when the recommendation means narrows down the destination information DN or service information based on the estimation model EM of the attribute information AT within a predetermined similar range based on the user's attribute information AT, the destination information DN or service information with a proven track record of increasing the well-being value is given priority over other destination information DN or service information and displayed on the display unit 111 of the user terminal 110 for recommendation. By doing so, the well-being value of the user can be further gradually increased, the essential happiness of the user can be enhanced, and the monetary consumption in the recommended destination or service can be increased to further promote the activation of the local economy and market.

[0085] Also, on the display unit 111 of the user terminal 110, the destination information DN with a proven track record of increasing the well-being value can be freely displayed on the map and is displayed in a form that changes according to the number of proven records of increasing the well-being value. By doing so, the user can understand the destination information DN with a proven track record at a glance, stimulate the user's motivation to act, further promote the activation of the local economy, and visually appeal to the user the characteristics of the businesses in that area.

[0086] Also, the program (information processing method) of the recommendation system 100 which is an embodiment of the present invention includes a predetermined operation presence / absence determination step S3 for determining whether or not current situation information ST of a user is input as an example of a predetermined operation in the user terminal 110, and when there is a predetermined operation, in the user terminal 110 or the server 120, an estimated model selection step S4 in which the recommendation means selects an estimated model EM of attribute information AT within a predetermined similar range based on the user's attribute information AT which has been input in advance, a similar range destination / service narrowing-down step S5 in which the recommendation means narrows down destination information DN or service information with an increased well-being value based on the estimated model EM of attribute information AT within a predetermined similar range based on the user's attribute information AT, and a similar attribute destination / service recommendation display step S6 in which the user terminal 110 displays the narrowed-down destination information DN or service information on the display unit 111 of the user terminal 110 to make a recommendation. By having these steps, it is possible to increase the happiness of a large number of users whose attribute information AT is similar to the attribute related to the estimated model EM, increase the user's actions and increase the monetary consumption for the means of transportation or at the destination or service, thereby further promoting the activation of the regional economy and market, it is possible to confirm whether or not a user who wants to improve the well-being value has come to that area, and it is possible to give advice on marketing to the businesses in that area, etc., and its effect is enormous.

Explanation of Signs

[0087] 100 ··· Recommendation system 110 ··· User terminal 111 ··· Display unit 112 ··· My page screen 113 ··· Your mood screen 114 ··· Recommendation screen 115 ··· Satisfaction evaluation input window 116 ··· Search screen 120 ··· Server 121 ··· Database 130 ··· Store terminal (product / service / location provider terminal) ST ··· Situation information LK ··· Preference information RT ··· Route information DN ··· Destination information IC ··· Icon (of destination information) TP ··· User type trend information AT ··· Attribute information CA ··· Category-specific action information SF ··· Satisfaction evaluation information (action value information) EM ··· Estimation model

Claims

1. A recommendation system comprising a user terminal and a server, which recommends a destination or a service to a user, There is an estimation model that pre-estimates well-being values based on user attribute information and category-based behavior information, When a predetermined operation occurs in the user terminal, in the user terminal or the server, the recommendation means selects an estimation model of attribute information within a predetermined similarity range based on the user's attribute information, and increases the well-being value based on the estimation model of attribute information within a predetermined similarity range based on the user's attribute information. The destination information or service information is narrowed down, and the narrowed-down destination information or service information is displayed on the display unit of the user terminal to make a recommendation. A recommendation system characterized by this configuration.

2. When it is determined that the destination recommended based on the current location information of the user terminal has been reached, or when it is determined that the service application operation recommended by the user terminal has been completed, the user terminal or the server uses the category-based behavior information of the user by the recommendation, the user's attribute information, and the user's attribute information. A well-being value correlated with the satisfaction degree is calculated based on the corresponding estimation model, and is stored in the database in association with the attribute information and the destination information or service information. The recommendation system according to claim 1, characterized by this configuration.

3. When it is determined that the destination recommended based on the current location information of the user terminal has been reached, or when it is determined that the service application operation recommended by the user terminal has been completed, the evaluation items of the satisfaction degree are displayed on the display unit of the user terminal, When the action value information, which is the evaluation information of the satisfaction degree, is input, the user terminal or the server calculates a well-being value correlated with the satisfaction degree based on the category-based behavior information of the user by the recommendation, the input action value information, the user's attribute information, and the estimation model corresponding to the user's attribute information, and stores it in the database in association with the attribute information and the destination information or service information. The recommendation system according to claim 2, characterized by this configuration.

4. The recommendation system according to claim 2 or claim 3, characterized in that the recommendation means displays, on the display unit of the user terminal, reason information related to an index item of a well-being value correlated with the satisfaction degree, in addition to the destination information or the service information.

5. The recommendation system according to claim 2 or claim 3, characterized in that the user terminal or the server is configured to feedback the well-being values of users accumulated in the database according to different attribute information to the estimation model according to different attribute information.

6. When the recommendation means narrows down the destination information or the service information based on the estimation model of the attribute information within a predetermined similar range based on the user's attribute information, the destination information or the service information with a proven track record of increased well-being value is prioritized over other destination information or service information, and is displayed on the display unit of the user terminal for recommendation. The recommendation system according to claim 2 or claim 3 is characterized by this configuration.

7. The recommendation system according to claim 2 or claim 3, characterized in that on the display unit of the user terminal, the destination information with a proven track record of increased well-being value can be freely displayed on the map, and is displayed in a form that changes according to the number of proven track records of increased well-being value.

8. A program for a recommendation system that includes a user terminal and a server and recommends a destination or a service to a user, A predetermined operation presence / absence determination step for determining whether or not there has been a predetermined operation in the user terminal, When the predetermined operation has occurred, in the user terminal or the server, an estimation model selection step in which the recommendation means selects an estimation model of the attribute information within a predetermined similar range based on the user's attribute information that has been input in advance, A similar range destination / service narrowing step in which the recommendation means narrows down the destination information or the service information with an increased well-being value based on the estimation model of the attribute information within a predetermined similar range based on the user's attribute information A program of a recommendation system, characterized by having a similar attribute destination / service recommendation display step in which the user terminal displays the filtered destination information or service information on the display unit of the user terminal to make a recommendation.

9. An information processing method for recommending a destination or service to a user, comprising: a step of determining whether or not a predetermined operation has occurred in the user terminal; when the predetermined operation has occurred, a step in which a recommendation means in the user terminal or the server selects an estimation model of attribute information within a predetermined similar range based on the user's attribute information, based on the pre-input user's attribute information; a step in which the recommendation means filters destination information or service information with an increased well-being value based on an estimation model of attribute information within a predetermined similar range based on the user's attribute information; and a step in which the user terminal displays the filtered destination information or service information on the display unit of the user terminal to make a recommendation.

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