Recommendation system and program thereof

Abstract

To provide a recommendation system that enhances the essential level of happiness of a user by considering a relation between a behavior associated with a previous recommendation and that associated with a later recommendation.SOLUTION: A recommendation system 100 includes a user terminal 110 and a server 120, wherein recommendation means provided in the user terminal or the server displays route information RT and destination information DN as a set on a display unit 111 of the user terminal for making an n-th recommendation, estimates information about a health status of a user based on information obtained from the user terminal at timing before the n-th recommendation, estimates information about a change in the health status of the user due to user's actions following the n-th recommendation based on information obtained from the user terminal after the n-th recommendation, narrows down destination information considering such estimated information, and narrows down the route information including transportation means information to make an n+1-th recommendation.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 destinations to a user, and a program therefor. [Background technology]

[0002] Conventionally, there have been programs that suggest suitable destinations for users (for example, Patent Document 1). There is also a program that provides route information that matches the travel preferences and behavioral tendencies of an individual user (for example, Patent Document 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-076979 [Patent Document 2] Patent Publication No. 2021-043511 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when a user travels to a destination according to the first suggestion, achieves their goal, and then decides on their next destination, they use the program again to receive a second suggestion. However, the only thing that is common between the travel and destination suggested by the first suggestion and the travel and destination suggested by the second suggestion is preferences, and the user's intrinsic happiness is not fully taken into consideration.

[0005] Therefore, the present invention is intended to solve the problems of the conventional technology as described above. In other words, the object of the present invention is to provide a recommendation system and a program therefor that can increase a user's intrinsic happiness by taking into account the relationship between actions based on earlier recommendations and actions based on later recommendations. [Means for solving the problem]

[0006] The invention according to claim 1 is a recommendation system that includes a user terminal and a server and recommends destinations to a user, wherein a recommendation means having artificial intelligence provided in the user terminal or the server displays route information and destination information as a set on a display unit of the user terminal to make an n-th recommendation, and the recommendation means determines or estimates information related to the user's health condition based on information input by the user terminal or information obtained from the user terminal before making the n-th recommendation, and the recommendation means determines or estimates information related to the user's health condition based on information input by the user terminal after the n-th recommendation. The above-mentioned problem is solved by the recommendation means being configured to determine or estimate information regarding changes in the user's health condition due to the user's behavior in line with the nth recommendation based on information stored in the user terminal or information obtained from the user terminal, and to narrow down destination information and route information including transportation information by taking into consideration information regarding the user's health condition before the nth recommendation and information regarding changes in the user's health condition due to the user's behavior in line with the nth recommendation, and to display the narrowed down route information and destination information as a set on the display unit of the user terminal to make the n+1th recommendation.

[0007] The invention of claim 2 further solves the above-mentioned problem by being configured such that, in addition to the configuration of the recommendation system described in claim 1, when the recommendation means determines or estimates that the user's health condition has improved due to the user's behavior in line with the nth recommendation, compared to information about the user's health condition at the time before the nth recommendation was made, the recommendation means selects transportation means information for the n+1th recommendation that is different from the transportation means information for the nth recommendation.

[0008] The invention of claim 3 further solves the above-mentioned problem by, in addition to the configuration of the recommendation system described in claim 2, being configured such that the recommendation means determines or estimates information regarding the user's health condition at the time before the nth recommendation is made based on at least one of the user's schedule information, activity information estimated from location information and staying time information of the user's terminal, and health-related input information on the user's terminal.

[0009] The invention of claim 4 further solves the above-mentioned problem by being configured in such a way that, in addition to the configuration of the recommendation system described in claim 3, when the destination of the nth recommendation is an event venue, the recommendation means selects transportation means information for the n+1th recommendation that is different from transportation means information recommended to other users in relation to the other users, or selects use start time information different from the transportation means use start time information, thereby controlling the flow of people and avoiding congestion.

[0010] The invention according to claim 5 is a program for a recommendation system that recommends destinations to a user, comprising: an n-th recommendation step in which recommendation means having artificial intelligence provided in a user terminal or a server displays route information and destination information as a set on a display unit of the user terminal to make an n-th recommendation; a pre-n-th recommendation health condition determination / estimation step in which the recommendation means determines or estimates information relating to the user's health condition based on information input by the user terminal or information obtained from the user terminal before making the n-th recommendation; and a pre-n-th recommendation health condition determination / estimation step in which the recommendation means determines or estimates information relating to the user's health condition based on information input by the user terminal after the n-th recommendation, or The above-mentioned problem is solved by having a health condition determination / estimation step during n-th recommendation action, which determines or estimates information regarding changes in the user's health condition due to the user's behavior in line with the n-th recommendation based on information obtained from the user terminal, and an n+1th recommendation step in which the recommendation means narrows down destination information and route information including transportation means information, taking into account information regarding the user's health condition before the n-th recommendation and information regarding changes in the user's health condition due to the user's behavior in line with the n-th recommendation, and displays the narrowed down route information and destination information as a set on the display unit of the user terminal to make the n+1th recommendation. Effect of the Invention

[0011] The recommendation system of the present invention is equipped with a user terminal and a server, and is not only able to recommend destinations to users by communicating between the user terminal and the server, but can also provide the following unique effects.

[0012] According to the recommendation system of the invention of claim 1, a determination is made as to whether the user's health condition is improving based on the user's physical, mental, mental, etc. health condition before (initial) taking action in accordance with a recommendation, and the user's physical, mental, mental, etc. health condition while taking action in accordance with the recommendation, and a so-called next-next recommendation is presented based on the state before the previous recommendation. This makes it possible to increase the user's intrinsic happiness by taking into account the relationship between actions based on the previous recommendation and actions based on the subsequent recommendation.

[0013] According to the recommendation system of the invention of claim 2, in addition to the effects of the invention of claim 1, the means of moving between earlier recommendations is different from the means of moving between later recommendations, and at least one of the user's physical load, mental load, and spiritual load does not change and the load does not become too large or too small, so that the user can obtain moderate stimulation and increase the user's intrinsic happiness.

[0014] According to the recommendation system of the invention of claim 3, in addition to the effect of the invention of claim 2, what the user was doing and what their health condition was before the trip (before moving according to the recommendation) is determined and estimated based on schedule information and sensor information, so that the nth recommendation and the n+1th recommendation appropriate to the user's health condition can be made.

[0015] According to the recommendation system of the invention of claim 4, in addition to the effects of the invention of claim 3, even if the destination is crowded, the transportation means information and the start time information of the transportation means used when moving from that location to the next recommended destination will be different from those of other users, so that the flow of people can be controlled to avoid heavy congestion.

[0016] According to the program of the recommendation system of the invention of claim 5, similar to the effect achieved by the invention of claim 1, a determination is made as to whether the user's health condition is improving or not based on the user's physical, mental, mental, etc. health condition before (initial) taking action in accordance with a recommendation, and the user's physical, mental, mental, etc. health condition while taking action in accordance with the recommendation, and a so-called next-next recommendation is presented based on the state before the previous recommendation, thereby making it possible to increase the user's intrinsic happiness by taking into account the relationship between actions based on a previous recommendation and actions based on a later recommendation. [Brief description of the drawings]

[0017] [Figure 1] FIG. 1 is a diagram showing the concept of a recommendation system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a chart showing an example of the operation of the recommendation system according to the embodiment of the present invention. [Diagram 3] FIG. 2 is a diagram showing a My Page screen of the recommendation system according to an embodiment of the present invention. [Figure 4] FIG. 13 is a diagram showing a "Your Mood" screen of the recommendation system according to the embodiment of the present invention. [Diagram 5] FIG. 2 is a diagram showing a recommendation screen of the recommendation system according to an embodiment of the present invention. [Figure 6] FIG. 2 is a conceptual diagram showing the relationship between an nth recommendation and an (n+1)th recommendation in a recommendation system according to an embodiment of the present invention. [Figure 7] FIG. 13 is a diagram showing examples of parameter items taken into consideration in the relationship between an nth recommendation and an (n+1)th recommendation in the recommendation system according to an embodiment of the present invention. [Figure 8] FIG. 13 is a diagram showing examples of parameter items of transportation means taken into consideration in the relationship between the nth recommendation and the (n+1)th recommendation in the recommendation system according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] The recommendation system of the present invention includes a user terminal and a server, and a recommendation means having artificial intelligence provided in the user terminal or the server displays route information and destination information as a set on a display unit of the user terminal to make an n-th recommendation, and the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal or information obtained from the user terminal before making the n-th recommendation, and the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal or information obtained from the user terminal after the n-th recommendation, and recommends the user's health condition based on the user's behavior in accordance with the n-th recommendation based on information input by the user terminal or information obtained from the user terminal after the n-th recommendation. The specific implementation of the system is not critical as long as it is configured to determine or estimate information regarding changes in the user's health condition, and the recommendation means narrows down destination information and route information including transportation information by taking into account information regarding the user's health condition before the nth recommendation and information regarding changes in the user's health condition due to the user's behavior in accordance with the nth recommendation, and displays the narrowed down route information and destination information as a set on the display unit of the user terminal to make the n+1th recommendation, thereby increasing the user's intrinsic happiness by taking into account the relationship between behavior due to a previous recommendation and behavior due to a later recommendation. Furthermore, the program of the recommendation system of the present invention includes an n-th recommendation step in which recommendation means having artificial intelligence provided in a user terminal or a server displays route information and destination information as a set on a display unit of the user terminal to make an n-th recommendation; a pre-n-th recommendation health condition determination / estimation step in which the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal or information obtained from the user terminal before making the n-th recommendation; and a pre-n-th recommendation health condition determination / estimation step in which the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal or information obtained from the user terminal after the n-th recommendation, based on information input by the user terminal or information obtained from the user terminal. The specific implementation of the system may be any as long as it has a health condition determination / estimation step during the nth recommendation action, which determines or estimates information regarding changes in condition, and an n+1th recommendation step, in which the recommendation means takes into account information regarding the user's health condition before the nth recommendation and information regarding changes in the user's health condition due to the user's action in accordance with the nth recommendation, narrows down destination information and route information including transportation information, and displays the narrowed down route information and destination information as a set on the display unit of the user terminal to make the n+1th recommendation, thereby enabling the user's intrinsic happiness to be increased by taking into account the relationship between actions due to previous recommendations and actions due to subsequent recommendations.

[0019] For example, the user terminal may be a notebook type personal computer terminal, a smartphone terminal, a tablet terminal, a wristwatch type terminal, a glasses type terminal, or the like, which has a display unit and an operating unit and transmits and receives information, and may be any terminal that can be freely connected to a server via a communication network including a wide area network, such as the Internet, a local network, or a telephone line. Furthermore, 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. EXAMPLES

[0020] A recommendation system 100 according to an embodiment of the present invention will be described below with reference to FIGS. Here, FIG. 1 is a diagram showing the concept of the recommendation system 100 which is an embodiment of the present invention, FIG. 2 is a chart diagram showing an example of the operation of the recommendation system 100 which is an embodiment of the present invention, FIG. 3 is a diagram showing a My Page screen 112 of the recommendation system 100 which is an embodiment of the present invention, FIG. 4 is a diagram showing a Your Mood screen 113 of the recommendation system 100 which is an embodiment of the present invention, FIG. 5 is a diagram showing a recommendation screen 114 of the recommendation system 100 which is an embodiment of the present invention, FIG. 6 is a conceptual diagram showing the relationship between the nth recommendation and the n+1th recommendation of the recommendation system 100 which is an embodiment of the present invention, FIG. 7 is a diagram showing an example of parameter items considered in the relationship between the nth recommendation and the n+1th recommendation of the recommendation system 100 which is an embodiment of the present invention, and FIG. 8 is a diagram showing an example of parameter items of transportation means considered in the relationship between the nth recommendation and the n+1th recommendation of the recommendation system 100 which is an embodiment of the present invention.

[0021] A recommendation system 100 according to an embodiment of the present invention includes a user terminal 110 and a server 120, as shown in FIG. The user terminal 110 is arranged to be able to communicate with the server 120 . The server 120 includes a database 121 . The recommendation system 100 is configured to recommend destinations to the user based on a database 121 that registers the latest information on products, services, locations, etc. input from a store terminal (not shown) or the like.

[0022] More specifically, first, the user logs in to the recommendation system 100 at the user terminal 110 . Then, the user's preference information LK is input in advance. For example, in the "Favorite Things" 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, cafes, outdoors, shopping, going out, entertainment, fashion, indoors, etc., and within each category, multiple photos with content related to that category are displayed. The user then selects one or more photos that depict something they like. Each photo is tagged with information that indicates what is shown in it. When a photo is selected by the user, tag information of the selected photo is added as preference information LK, which is information on the user's favorite things.

[0023] In addition to photos, icons, keywords, sounds, etc. may be selected. The icons, keywords, and sounds all represent something. In the case of audio, a button is displayed so that when the button is operated, some kind of audio is output, and when the button is selected, tag information of the button content is added as preference information LK. In addition, the user may use the microphone in the user terminal 110 to input voice input about things they like, or may use the input keys to input text about things they like in sentences or words, and this information may be added as preference information LK.

[0024] Furthermore, a "Your Personality" screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110 includes a number of simple questions. For example, questions include, "I like meeting new people and can enjoy conversations with people even when meeting them for the first time." As an example, the system is designed to allow users to intuitively answer each question using a five-point scale, such as not at all applicable, hardly applicable, indeterminate, somewhat applicable, or completely applicable. When the user inputs these answers, a recommendation means having artificial intelligence in the user terminal 110 or the server 120 analyzes the answer information and obtains user type tendency information TP.

[0025] Thereafter, when the user's current situation information ST is input in the user terminal 110 as an operation to request a recommendation, a recommendation means having artificial intelligence in the user terminal 110 or the server 120 narrows down the destination information DN based on the user's preference information LK input in advance, the inputted user's current situation information ST, and the current location information of the user terminal 110, taking into consideration the means of transportation information. At the same time, the recommendation means narrows down the route information RT including the transportation means information. Here, narrowing down the information may be achieved by reducing a large number of pieces of information to a small number of pieces of information, where the small number is one or more pieces of information. The destination information DN and route information RT before narrowing down are not limited to those in the database 121, and may be information in another system or information in a social networking service. The recommendation means is configured to display the narrowed-down route information RT and destination information DN as a set on the display unit 111 of the user terminal 110 and recommend them.

[0026] In this way, when the user performs an operation to request a recommendation for the first time (nth time: n is a natural number), a recommendation means having artificial intelligence provided in the user terminal 110 or the server 120 displays the route information RT and destination information DN as a set on the display unit 111 of the user terminal 110 to make the nth recommendation.

[0027] Furthermore, in the present invention, the recommendation means determines or estimates information relating to the user's health condition based on information input by the user terminal 110 at a timing before making the nth recommendation. It should be noted that, instead of the information inputted by the user terminal 110, information relating to the user's health condition may be determined or estimated based on information obtained from the user terminal 110. Furthermore, the recommendation means determines or estimates information regarding a change in the user's health condition due to the user's behavior in accordance with the nth recommendation, based on information input by the user terminal 110 after the nth recommendation. It should be noted that, instead of the information input by the user terminal 110, information regarding the change in the user's health condition due to the user's behavior in accordance with the nth recommendation may be determined or estimated based on information obtained from the user terminal 110.

[0028] Next, the recommendation means narrows down the destination information DN and also narrows down the route information RT including the transportation means information, taking into consideration information on the user's health condition before the nth recommendation and information on the change in the user's health condition due to the user's behavior in accordance with the nth recommendation. The recommendation means is configured to display the narrowed-down route information RT and destination information DN as a set on the display unit 111 of the user terminal 110 to make the (n+1)th recommendation.

[0029] This allows the system to determine whether the user's health condition is improving based on the user's physical, mental, mental, etc. health condition before (initial) taking action in accordance with a recommendation, and the user's physical, mental, mental, etc. health condition while taking action in accordance with that recommendation, and then presents a so-called next-next recommendation based on the state before the previous recommendation. As a result, it is possible to increase the user's intrinsic happiness by taking into account the relationship between actions based on earlier recommendations and actions based on later recommendations.

[0030] Next, an example of the operation of the recommendation system 100 of the present invention will be described in more detail. As shown in Figure 2, in step S1, which is a recommendation request operation determination step (nth recommendation step), the user terminal 110 or the server 120 determines whether the user's current situation information ST has been input in the user terminal 110 as an operation to request the recommendation described above. Here, prior to performing an operation to request a recommendation, the user performs an operation to select a photo on the "Favorite Things" screen described above, for example. Then, the user terminal 110 or the server 120 registers the user's preference information LK in the database 121 in the server 120. Then, as shown in FIG. 3, when the user's preference information LK is registered, the user's preference information LK is displayed on a 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 a photo selected by the user is registered as the preference information LK, and the tag information is displayed in the "Favorite things and events" section.

[0031] In addition, the recommendation means may be configured to display user type tendency information TP obtained based on the answer information provided on the aforementioned “Your Personality” screen (not shown) in the “Your Personality” section of the My Page screen 112. As an example, the user type tendency information TP has items such as openness, conscientiousness, extroversion, agreeableness, and neuroticism, and is configured to be displayed as a level value for each item. The user type tendency information TP is configured to be registered in the database 121 in the server 120, similar to the user preference information LK.

[0032] Then, the user terminal 110 or the server 120 determines whether or not the user has input the current situation information ST of the user in the user terminal 110 as an operation to request a recommendation. For example, as shown in FIG. 4, a "Your Mood" screen 113 of the recommendation system 100 displayed on the display unit 111 of the user terminal 110 is provided in which the user's current situation information ST can be freely input. The "Your Mood" screen 113 has items for inputting information about people you are with, free time information, appetite and material desire information, and activity and rest desire information. For the information about people you are with, for example, options are set such as alone, couple, friends, and family, which indicate whether you are alone or who you are with. Furthermore, in the item of free time information, the current amount of free time can be freely input.

[0033] In addition, the appetite and material desire information items are provided with the option to freely input which of the two is given more weight. Furthermore, the active / rest desire information section allows users to freely input which of the two they would like to give more weight to. When an input operation is performed for these, the user terminal 110 or the server 120 determines that the user's current situation information ST has been input. If it is determined that an input operation has been made as an operation requesting a recommendation, the process proceeds to step S2. On the other hand, if it is determined that no input operation has been made yet, step S1 is repeated.

[0034] In addition, items may be provided for inputting the user's current situation information ST regarding whether or not the user is currently using a car or a motorcycle, the user's baggage information, the user's level of fatigue, the number of steps traveled, and calorie intake information. Furthermore, the user's current situation information ST may be not only information input by the user, but also current location information, date and time information, weather and temperature information, electronic payment information such as IC card and electronic money, etc., which may be automatically input. In addition, basically, the user travels from the current location to the destination during free time, has some kind of experience at the destination, and then travels from the destination to the current location and returns, but in order to accommodate cases where the user does not return to the current location, a field may be provided for inputting information about the user's final destination.

[0035] For example, you can use this service when your final destination is already decided and you want to use your free time to travel to your final destination via another destination. The method of inputting the information may involve taking a picture of the user's facial expression using the camera of user terminal 110, and estimating and inputting the fatigue level information using image analysis. Furthermore, information on the number of steps traveled may be input using walking history information of a pedometer function of the user terminal 110, and fatigue level information may be estimated. Furthermore, the distance traveled may be estimated based on the location information of the user terminal 110, calorie consumption information may be estimated, and fatigue level information may be estimated. Furthermore, the camera of the user terminal 110 may be used to take a picture of food or other ingested items, and calorie intake information may be estimated using image analysis.

[0036] Furthermore, the device may be configured so that the user's body temperature information, heart rate information, travel distance information, number of steps traveled, and the like are input using a smart watch terminal, which is a wristwatch-type terminal worn on the user's wrist. Also, a camera may be used to take a picture of the user's baggage, and the baggage information may be estimated and input using image analysis. Furthermore, a camera may be used to take pictures of cars and motorcycles, and image analysis may be used to estimate and input information on whether a car or motorcycle is currently being used. Furthermore, the input is not limited to that by a user operation. For example, the information may be configured to be input automatically at all times, or may be configured to be input automatically when the application of the recommendation system 100 is started.

[0037] In step S2, as the nth recommendation step, a recommendation means having artificial intelligence provided in the user terminal 110 or the server 120 displays the route information RT and the destination information DN as a set on the display unit 111 of the user terminal 110 to make the nth recommendation. More specifically, in the user terminal 110 or the server 120, a recommendation means having artificial intelligence narrows down the destination information DN based on the user's preference information LK input in advance, the input current situation information ST of the user, and the current location information of the user terminal 110, taking into consideration the means of transportation information. At the same time, the recommendation means narrows down the route information RT including the transportation means information. The destination information DN may be registered in the database 121 of the server 120 or may be on a social networking service (SNS), and is narrowed down from among them. In other words, in cooperation with another system, destination information DN registered in the other system may be narrowed down and picked up. In addition, the destinations may be narrowed down by taking into consideration transportation information from other systems.

[0038] For example, it takes into account information on train, subway, and bus timetables, transfer time information, delay information, road traffic volume and congestion information, congestion forecast information, information on available rental cars at the nearest location, taxi dispatch information in the area, and parking information at the destination and its surrounding areas. As a more specific example, if the next train is a local train and the next one is an express train, using the express train will allow you to travel farther and return within the available time frame compared to using a local train. In addition, the case where the bus arrives at a bus stop close to the current location information, and therefore the recommended destination farthest from the current location among the narrowed-down destination information DNs is the easiest and most suitable, is also taken into consideration. When narrowing down the destination information DN in consideration of the transportation information, campaign information such as free, discount, coupons, etc. for the transportation means and destinations, which is an example of information that is useful to the user, may be picked up and incorporated.

[0039] Then, the user terminal 110 displays the narrowed-down route information RT and the destination information DN as a set on the display unit 111 of the user terminal 110 and recommends them. As shown in FIG. 5, as an example, the display unit 111 of the user terminal 110 displays a recommendation screen 114. The recommendation screen 114 displays map information including the current location of the user terminal 110, an icon IC of one or more pieces of narrowed-down destination information DN, and route information RT from the current location to one or more destinations.

[0040] In step S3, which is a step for determining whether or not the user has started moving in accordance with the recommendation, the user terminal 110 or the server 120 determines, based on a change in the location information of the user terminal 110, whether or not the user has started moving in accordance with the recommendation, as a step for determining whether or not the user has started moving in accordance with the recommendation. If it is determined that the movement has started, the process proceeds to step S4, whereas if it is determined that the movement has not started yet, step S3 is repeated.

[0041] In step S4, as a pre-nth recommendation health condition determination / estimation step, the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal 110 at the timing before making the nth recommendation. It should be noted that, instead of the information inputted by the user terminal 110, information relating to the user's health condition may be determined or estimated based on information obtained from the user terminal 110. For example, the user terminal 110 may be configured to display a screen for inputting a health condition on the display unit 111 before making the nth recommendation, to prompt the user to input information about the health condition.

[0042] Additionally, for example, a user terminal 110 such as a smart watch or a smart ring may determine or estimate information regarding the user's health condition based on information such as the user's heart rate information, sleep time information, blood pressure information, and information about the quality of sleep. Furthermore, for example, based on the location information of the user terminal 110 from the previous night, the order details can be ascertained from information such as a two-hour stay at a yakiniku restaurant and payment information made at the yakiniku restaurant using a payment app or credit card, and the calorie intake from the previous night and the amount of alcohol consumed can be estimated. Using these techniques, it is possible to estimate the health state at the time of the nth recommendation, such as feeling a bit hungover, sleep-deprived, tired, or having eaten a little too much.

[0043] In step S5, as a health condition determination / estimation step during the nth recommendation behavior, the recommendation means determines or estimates information regarding changes in the user's health condition due to the user's behavior in accordance with the nth recommendation based on the information input by the user terminal 110 after the nth recommendation. It should be noted that, instead of the information input by the user terminal 110, information regarding the change in the user's health condition due to the user's behavior in accordance with the nth recommendation may be determined or estimated based on information obtained from the user terminal 110. For example, the user terminal 110 may be configured to display a screen for inputting changes in health condition on the display unit 111 after the nth recommendation and the user starts moving, to prompt the user to input information about the changes in health condition. In addition, for example, a user terminal 110 such as a smart watch or a smart ring may determine or estimate information regarding changes in health condition based on information such as the user's heart rate information, pedometer function information, calorie consumption information, sleep time information, blood pressure information, and information about sleep quality.

[0044] In step S6, which is the (n+1)th recommendation step, the recommendation means narrows down the destination information DN and also narrows down the route information RT including transportation information, taking into consideration information regarding the user's health condition before the nth recommendation and information regarding changes in the user's health condition due to the user's behavior in accordance with the nth recommendation. Then, the recommendation means displays the narrowed-down route information RT and the destination information DN as a set on the display unit 111 of the user terminal 110 to make the (n+1)th recommendation. The display method is the same as recommendation screen 114 for the nth recommendation shown in FIG.

[0045] As shown in FIG. 6, for example, assume that the user is feeling hungover, and therefore, in the first (n-th) recommendation, travel by train is recommended as a means of transportation, taking into consideration safety and health. If the change in the user's health condition is determined or estimated to be that the user is recovering from a hangover, walking may be recommended as a means of transportation to get the user moving and improve their physical, mental, and spiritual well-being.

[0046] As described above, this allows a determination to be made as to whether the user's health condition is improving based on the user's physical, mental, mental, etc. health condition before (initial) taking action in accordance with a recommendation, and the user's physical, mental, mental, etc. health condition while taking action in accordance with that recommendation, and a so-called next-next recommendation is presented based on the state before the previous recommendation. As a result, it is possible to increase the user's intrinsic happiness by taking into account the relationship between actions based on earlier recommendations and actions based on later recommendations.

[0047] Furthermore, in this embodiment, if the recommendation means determines or estimates that the user's health condition has improved due to the user's behavior in line with the nth recommendation, compared to information regarding the user's health condition at the time before the nth recommendation was made, the recommendation means is configured to select transportation means information for the n+1th recommendation that is different from the transportation means information for the nth recommendation. For example, as shown in FIG. 7, the recommendation means has items of diet, body temperature, sleep, and fatigue as information related to health status, and items of hobbies, preferences, time, distance, weather, seasons, temperature, humidity, means of transportation, and destination as external factors. Each item has parameters for physical activity / rest, mental activity / rest, and mental activity / rest.

[0048] As shown in FIG. 8, the information on means of transportation includes items such as train, bus, taxi, shared bicycle, airplane, walking, kick scooter, and others. Each item has the parameters of being active, relaxing, fun, fast, cheap, not affected by weather, and low physical load. For example, if taxi travel is recommended as a means of transportation in the nth recommendation, walking is recommended as a means of transportation in the n+1th recommendation.

[0049] As a result, the means of movement of the earlier recommendation differs from the means of movement of the later recommendation, and at least one of the physical load, mental load, and mental load of the user is changed so that the load is not excessively large or small. As a result, the user can obtain the appropriate stimulation and increase the user's intrinsic happiness.

[0050] In addition, in this embodiment, the recommendation means is configured to determine or estimate information regarding the user's health condition at the time before the nth recommendation is made based on at least one of the user's schedule information, activity information estimated from location information and stay time information of the user terminal 110, and health-related input information in the user terminal 110.

[0051] This allows the system to determine and estimate what the user will be doing and their health condition before the trip (before moving according to recommendations) based on schedule information and sensor information. For example, based on information such as an example of schedule information that the user was (will be) kept busy for a long time at a restaurant for entertaining clients the previous night, it is determined or estimated that the user is feeling tired at the time of the nth recommendation. As described above, based on location information of user terminal 110 from the previous night, such as information that the user spent two hours at a yakiniku restaurant, the calorie intake from the previous night may be estimated, and further, the amount of alcohol consumed may be estimated. And it is possible to estimate the health state at the time of the nth recommendation, such as feeling a bit hungover, sleep-deprived, tired, or having eaten a little too much. As a result, it is possible to make nth and n+1th recommendations appropriate to the user's health condition.

[0052] In addition, if the recommendation means determines or estimates that the user's health condition has not improved due to the user's behavior in accordance with the nth recommendation, compared to information on the user's health condition before the nth recommendation, the recommendation means may be configured to select the transportation means information for the n+1th recommendation that has at least the same or smaller physical load, mental load, and mental load as the transportation means information for the nth recommendation. For example, if it is determined or estimated that the user's health condition has deteriorated due to the user's behavior in accordance with the nth recommendation, it is not advisable for the user to actively exercise. More specifically, it is assumed that the user's health state at the time before the nth recommendation is made is estimated to be a bit hungover and sleep-deprived.

[0053] Then, let us assume that the user's health state based on their behavior following the nth recommendation is estimated to be a bit hungover, sleep-deprived, and extremely fatigued. For example, information about changes in health condition, such as gradually becoming a little unsteady, gradually increasing heart rate, gradually slowing walking speed, etc., can be obtained from a sensor or the like of the user terminal 110. In addition to judging and estimating the user's health state resulting from the user's behavior in accordance with the nth recommendation by comparing it with information on the user's health state prior to the nth recommendation, it is also possible to judge and estimate changes in the user's health state resulting from the user's behavior in accordance with the nth recommendation.

[0054] In this case, for the (n+1)th recommended means of transportation information, a taxi or train is selected, which is a means of transportation with less physical strain. For example, if the transportation means information for the nth recommendation is a taxi, the same taxi may be selected as the transportation means information for the n+1th recommendation. This makes it possible to avoid, at least, the physical strain that would be imposed when moving along the next recommendation becoming greater than that imposed when moving along the previous recommendation. As a result, the user's health can be expected to gradually improve.

[0055] Similarly, if it is determined or estimated that the user's health condition has not improved as a result of the user's behavior in accordance with the nth recommendation, the destination information for the n+1th recommendation may be configured to select one that imposes at least the same or a smaller physical load among the physical load, mental load, and mental load compared to the destination information for the nth recommendation. This makes it possible to avoid, at least, the physical strain that would be imposed on the user when spending time at a destination in line with the next recommendation being greater than the physical strain that would be imposed when spending time at the destination of the previous recommendation. As a result, the user's health can be expected to gradually improve.

[0056] Furthermore, in this embodiment, when the destination of the nth recommendation is an event venue, the recommendation means is configured to select transportation means information for the n+1th recommendation that is different from the transportation means information recommended to other users in relation to the other users, thereby controlling the flow of people and avoiding congestion. In addition, depending on the relationship with other users, use start time information different from the use start time information of the means of transportation recommended to other users may be selected.

[0057] As a result, even if the destination is crowded, the transportation means information and the start time information of the transportation means used when traveling from that location to the next recommended destination will be different from that of other users. For example, if the destination is a concert hall where a live performance by a musical artist is taking place, bus stops and train stations near the venue tend to be crowded immediately after the performance ends. Therefore, for the transportation means information of the n+1th recommendation, a different transportation means is recommended in relation to other users, or the transportation means are recommended to be used with a time lag by varying the start time of use of the transportation means. As a result, the flow of people can be controlled to avoid large congestion.

[0058] The recommendation system 100 thus obtained as an embodiment of the present invention includes a user terminal 110 and a server 120, and a recommendation means having artificial intelligence provided in the user terminal 110 or the server 120 displays a set of route information RT and destination information DN on the display unit 111 of the user terminal 110 to make an n-th recommendation, and the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal 110 or information obtained from the user terminal 110 before making the n-th recommendation, and the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal 110 or information obtained from the user terminal 110 after the n-th recommendation. Based on the obtained information, information regarding changes in the user's health condition due to the user's behavior in line with the nth recommendation is determined or estimated, and the recommendation means narrows down the destination information DN and also narrows down the route information RT including transportation information, taking into account the information regarding the user's health condition before the nth recommendation and the information regarding changes in the user's health condition due to the user's behavior in line with the nth recommendation, and displays the narrowed down route information RT and destination information DN as a set on the display unit 111 of the user terminal 110 to make the n+1th recommendation, thereby making it possible to increase the user's intrinsic happiness by taking into account the relationship between behavior due to previous recommendations and behavior due to subsequent recommendations.

[0059] Furthermore, if the recommendation means determines or estimates that the user's health condition has improved due to the user's behavior in line with the nth recommendation, compared to information about the user's health condition before the nth recommendation, the recommendation means is configured to select transportation means information for the n+1th recommendation that is different from the transportation means information for the nth recommendation, thereby providing the user with a moderate stimulus and increasing the user's intrinsic happiness.

[0060] In addition, since the recommendation means is configured to determine or estimate information regarding the user's health condition at the time before making the nth recommendation based on at least one of the user's schedule information, activity information estimated from the location information and stay time information of the user terminal 110, and health-related input information in the user terminal 110, it is possible to make the nth recommendation and the n+1th recommendation appropriate according to the user's health condition.

[0061] Furthermore, when the destination of the nth recommendation is an event venue, the recommendation means selects transportation means information for the n+1th recommendation that is different from the transportation means information recommended to other users in relation to the other users, or selects use start time information different from the transportation means use start time information, thereby controlling the flow of people and avoiding congestion, thereby making it possible to control the flow of people and avoid major congestion.

[0062] Furthermore, the program of the recommendation system 100 according to the embodiment of the present invention includes n-th recommendation steps S1, S2 in which a recommendation means having artificial intelligence provided in the user terminal 110 or the server 120 displays a set of route information RT and destination information DN on the display unit 111 of the user terminal 110 to make an n-th recommendation, pre-n-th recommendation health condition determination / estimation steps S3, S4 in which the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal 110 or information obtained from the user terminal 110 at a timing before making the n-th recommendation, and n-th recommendation step S5, S6 in which the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal 110 or information obtained from the user terminal 110 after the n-th recommendation. The system has a health condition determination / estimation step S5 during n-th recommendation behavior, which determines or estimates information regarding changes in the user's health condition due to the user's behavior in line with the recommendation, and an n+1-th recommendation step S6 in which the recommendation means narrows down the destination information DN and narrows down the route information RT including transportation information, taking into account information regarding the user's health condition before the n-th recommendation and information regarding changes in the user's health condition due to the user's behavior in line with the n-th recommendation, and displays the narrowed down route information RT and destination information DN as a set on the display unit 111 of the user terminal 110 to make the n+1-th recommendation, thereby providing enormous benefits, such as the ability to increase the user's intrinsic happiness by taking into account the relationship between behavior due to a previous recommendation and behavior due to a later recommendation. [Explanation of symbols]

[0063] 100 ··· Recommendation System 110 User terminal 111... Display section 112 ··· My Page screen 113 Your Mood Screen 114 Recommendation screen 120 Server 121 ··· Database ST ··· Situation Information LK...Preference information RT Route information DN ··· Destination information IC ··· Icon TP User type trend information

Claims

1. A recommendation system that includes a user terminal and a server and recommends destinations to a user, A recommendation means having an artificial intelligence provided in the user terminal or the server displays the route information and the destination information as a set on a display unit of the user terminal to make an n-th recommendation; The recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal or information obtained from the user terminal before making the nth recommendation; The recommendation means determines or estimates information regarding a change in the user's health condition due to the user's behavior in accordance with the nth recommendation based on information input by the user terminal or information obtained from the user terminal after the nth recommendation; The recommendation system is characterized in that the recommendation means is configured to narrow down destination information and route information including transportation means information, taking into consideration information regarding the user's health condition before the nth recommendation and information regarding changes in the user's health condition due to the user's behavior in accordance with the nth recommendation, and to display the narrowed down route information and destination information as a set on the display unit of the user's terminal to make the n+1th recommendation.

2. The recommendation system described in claim 1 is configured to select transportation means information for the (n+1)th recommendation that is different from the transportation means information for the nth recommendation when the recommendation means determines or estimates that the user's health condition has improved due to the user's behavior in accordance with the nth recommendation, compared to information on the user's health condition at the time before the nth recommendation.

3. The recommendation system described in claim 2, characterized in that the recommendation means is configured to determine or estimate information regarding the user's health condition at the time before making the nth recommendation based on at least one of the user's schedule information, activity information estimated from location information and stay time information of the user's terminal, and health-related input information on the user's terminal.

4. The recommendation system of claim 3, characterized in that when the destination of the nth recommendation is an event venue, the recommendation means selects transportation information for the n+1th recommendation that is different from transportation information recommended to other users in relation to the other users, or selects use start time information different from the transportation use start time information, thereby controlling the flow of people and avoiding congestion.

5. A program for a recommendation system that recommends destinations to a user, an n-th recommendation step in which a recommendation means having an artificial intelligence provided in the user terminal or the server displays the route information and the destination information as a set on a display unit of the user terminal to make an n-th recommendation; a pre-n-th recommendation health condition determination / estimation step in which the recommendation means determines or estimates information regarding the user's health condition based on information input by the user terminal or information obtained from the user terminal before making the n-th recommendation; a health condition determination / estimation step during the n-th recommendation behavior in which the recommendation means determines or estimates information regarding a change in the user's health condition due to the user's behavior in accordance with the n-th recommendation based on information input by the user terminal after the n-th recommendation or information obtained from the user terminal; A program for a recommendation system, characterized in that the recommendation means has an n+1th recommendation step in which the recommendation means narrows down destination information and route information including transportation means information, taking into consideration information regarding the user's health condition before the nth recommendation and information regarding changes in the user's health condition due to the user's behavior in accordance with the nth recommendation, and displays the narrowed down route information and destination information as a set on the display unit of the user terminal to make the n+1th recommendation.

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