Recommendation device, system, method and program

Abstract

A recommendation device (1) comprises: an acquisition unit (11) that acquires state information indicating the current state of a predetermined user and including a health condition, vital data, a gait, or an impression of event participation; a determination unit (12) that uses the state information and personal information (address, medical information, preference, or family information) to determine recommendation information (event, medical institution / facility guidance information, product / service information, health information, etc.); and an output unit (13) that outputs the determined recommendation information to a predetermined output destination.

Description

[Technical Field]

[0001] The present invention relates to a recommendation device, system and method, and a computer-readable medium. [Background technology]

[0002] Patent Document 1 discloses a technology relating to a life support device that grasps the user's behavior, stress level, fatigue level, and other conditions, and provides life navigation services and displays advertisements in response to these conditions. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2001-344352 Summary of the Invention [Problem to be solved by the invention]

[0004] Here, the user's status may change when the user participates in a specific event, and therefore the services and information suitable for the user may differ depending on the user's status and how it has changed.

[0005] In view of the above-mentioned problems, an object of the present disclosure is to provide a recommendation device, system, method, and program for recommending appropriate information according to the user's state. [Means for solving the problem]

[0006] A recommendation device according to a first aspect of the present disclosure, An acquisition means for acquiring status information of a predetermined user; a determination means for determining recommendation information based on the state information; an output means for outputting the determined recommendation information to a predetermined output destination; Equipped with.

[0007] A recommendation system according to a second aspect of the present disclosure includes: a user terminal owned by a predetermined user; a recommendation device; The recommendation device acquiring means for acquiring status information of the user from the user terminal; a determination means for determining recommendation information based on the state information; an output means for outputting the determined recommendation information to a predetermined output destination; Equipped with.

[0008] A recommendation method according to a third aspect of the present disclosure includes: The computer Obtaining state information for a given user; determining recommendation information based on the state information; The determined recommendation information is output to a predetermined output destination.

[0009] A recommendation program according to a fourth aspect of the present disclosure includes: An acquisition process for acquiring status information of a predetermined user; a determination process for determining recommendation information based on the state information; an output process of outputting the determined recommendation information to a predetermined output destination; to be executed by the computer. [Effects of the Invention]

[0010] The present disclosure makes it possible to provide a recommendation device, system, method, and program for recommending appropriate information according to a user's state. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing the configuration of a recommendation device according to a first embodiment. [Figure 2] 1 is a flowchart showing the flow of a recommendation method according to the first embodiment. [Figure 3] FIG. 10 is a block diagram showing the overall configuration of a recommendation system according to a second embodiment. [Figure 4] FIG. 10 is a block diagram showing the configuration of a user terminal according to the second embodiment. [Figure 5] FIG. 10 is a block diagram showing the configuration of an authentication device according to a second embodiment. [Figure 6] FIG. 10 is a block diagram showing the configuration of a recommendation device according to a second embodiment. [Figure 7] 10 is a flowchart showing the flow of a user registration process according to the second embodiment. [Figure 8] 10 is a flowchart showing the flow of a face information registration process performed by the authentication device according to the second embodiment. [Figure 9] 10 is a flowchart showing the flow of a status reporting process according to the second embodiment. [Figure 10] 10 is a flowchart showing the flow of face authentication processing by the authentication device according to the second embodiment. [Figure 11] 10 is a flowchart showing the flow of a first recommendation process according to the second embodiment. [Figure 12] FIG. 10 is a diagram showing a display example of recommendation information according to the second embodiment. [Figure 13] FIG. 10 is a block diagram showing the overall configuration of a recommendation system according to a third embodiment. [Figure 14] 11 is a flowchart showing the flow of a second recommendation process according to the third embodiment. [Figure 15] FIG. 11 is a diagram showing an example of displaying index values ​​before and after participation according to the third embodiment. [Figure 16] FIG. 11 is a diagram showing a display example of recommendation information according to the third embodiment. [Figure 17] FIG. 10 is a block diagram showing the overall configuration of a recommendation system according to a fourth embodiment. [Figure 18] 13 is a flowchart showing the flow of a third recommendation process according to the fourth embodiment. [Figure 19] 13 is a flowchart showing the flow of a fourth recommendation process according to the fourth embodiment. [Figure 20] FIG. 13 is a diagram showing an example of a display of emotion distribution according to the fourth embodiment. [Figure 21]FIG. 13 is a diagram showing an example of a change in emotion distribution along a time series according to the fourth embodiment. [Figure 22] 13A and 13B are diagrams showing examples of display of the effect contents before and after the change and the reason for the change according to the fourth embodiment. [Figure 23] FIG. 13 is a diagram showing an example of a display of emotion distribution according to the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In each drawing, the same or corresponding elements are designated by the same reference numerals, and for clarity of explanation, duplicate explanations will be omitted as necessary.

[0013] <Embodiment 1> FIG. 1 is a block diagram showing the configuration of a recommendation device 1 according to the first embodiment. The recommendation device 1 is an information processing device that determines recommendation information suitable for a user according to status information such as the user's health condition and mood, and outputs (recommends) the information to the user and related parties. Here, the recommendation device 1 may be connected to a predetermined terminal via a communication network (not shown; hereinafter, the communication network may also be simply referred to as a network) or predetermined wireless communication. The network may be wired or wireless, and the type of communication protocol may be irrelevant. The terminal transmits status information of the user to the recommendation device 1. The terminal may also perform processing according to the output from the recommendation device 1. The terminal may be a user terminal carried or worn by the user.

[0014] The recommendation device 1 includes an acquisition unit 11, a determination unit 12, and an output unit 13. The acquisition unit 11 acquires state information of a predetermined user. Here, the state information is information indicating the current state of the user. For example, the state information may be the user's health condition, vital data and gait measured from the user's body, text information such as the user's current mood and thoughts about participating in an event input by the user, etc. However, the state information is not limited to these.

[0015] The determination unit 12 determines recommendation information based on the status information. Here, the recommendation information is information to be recommended (provided) to the user related to the status information. For example, the recommendation information may be information to guide events, medical institutions or facilities, information introducing products or services, and information provided about health. However, the recommendation information is not limited to these. The determination unit 12 may determine recommendation information using a recommendation model that inputs the status information and outputs recommendation information based on a predetermined logic. Note that publicly known technology such as an AI (Artificial Intelligence) model can be applied to the recommendation model. Furthermore, the recommendation model may be one that has been machine-learned using training data in which the status information and other information are used as input data and the results of adopting the recommendation information are used as correct answer data.

[0016] The output unit 13 outputs the determined recommendation information to a predetermined output destination. The predetermined output destination is, for example, a user terminal owned by the user related to the status information, an information processing device accessible to those related to the user (family, relatives, etc.), an information processing device accessible to those related to an event or facility related to the recommendation information, etc. However, the output destination is not limited to these.

[0017] 2 is a flowchart showing the flow of the recommendation method according to the first embodiment. First, the acquisition unit 11 acquires state information of a predetermined user (S11). Next, the determination unit 12 determines recommendation information based on the state information (S12). Then, the output unit 13 outputs the determined recommendation information to a predetermined output destination (S13).

[0018] In this way, the recommendation device 1 according to this embodiment determines recommended information in consideration of the state information acquired from the user, and therefore can recommend appropriate information according to the state of the user.

[0019] The recommendation device 1 includes a processor, a memory, and a storage device, which are not shown in the figure. The storage device stores a computer program that implements the processing of the recommendation method according to this embodiment. The processor then loads the computer program from the storage device into the memory and executes the computer program. As a result, the processor realizes the functions of an acquisition unit 11, a determination unit 12, and an output unit 13.

[0020] Alternatively, each component of the recommendation device 1 may be realized by dedicated hardware. Also, some or all of the components of each device may be realized by general-purpose or dedicated circuits, processors, etc., or a combination of these. These may be configured by a single chip, or may be configured by multiple chips connected via a bus. Some or all of the components of each device may be realized by a combination of the above-mentioned circuits, etc., and programs. Also, a CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), quantum processor (quantum computer control chip), etc. can be used as the processor.

[0021] Furthermore, when some or all of the components of the recommendation device 1 are realized by multiple information processing devices, circuits, etc., the multiple information processing devices, circuits, etc. may be centrally or distributed. For example, the information processing devices, circuits, etc. may be realized in a form in which each is connected via a communication network, such as a client-server system or a cloud computing system. Furthermore, the functions of the recommendation device 1 may be provided in a SaaS (Software as a Service) format.

[0022] <Embodiment 2> The present embodiment 2 is a specific example of the above-described embodiment 1. Fig. 3 is a block diagram showing the overall configuration of a recommendation system 1000 according to the present embodiment 2. The recommendation system 1000 is an information system for determining recommended information suitable for the user U0 according to the user U0's status information and personal information, and making recommendations to the user U0 and related parties.

[0023] The recommendation system 1000 includes a user terminal 100, an authentication device 200, and a recommendation device 300. The user terminal 100, the authentication device 200, and the recommendation device 300 are connected to each other via a network N. Here, the network N is a wired or wireless communication line, for example, the Internet.

[0024] In the following description, "personal authentication information" refers to information used for personal authentication (personal authentication, personal identification processing, etc.) and is information for uniquely identifying (identifying) a person. In this embodiment, personal authentication is described as facial authentication, which is an example of biometric authentication, and personal authentication information (personal identification information) is described as facial feature information, which is an example of biometric information. However, other technologies using captured images of a person can be applied to biometric authentication and biometric information. For example, biometric information may be data (features) calculated from physical features unique to an individual, such as fingerprints, voiceprints, veins, retinas, irises, and palm patterns. Instead of biometric authentication, other personal authentication methods may be applied, and biometric information may also be other personal authentication information. Examples of personal authentication information include, but are not limited to, a user ID, a combination of an ID and a password, the contents of an identification card such as a My Number or a driver's license (identification number, etc., and password), an electronic certificate, and code information. The code information may be a two-dimensional code, such as a QR Code (registered trademark).

[0025] The user terminal 100 is an information terminal that is held, carried, operated, or worn by the user U0, and transmits and receives data to and from the recommendation device 300 via the network N by wireless communication. The user terminal 100 is a mobile phone terminal, a smartphone, a tablet terminal, a wearable terminal, or the like. The user terminal 100 may also perform short-range wireless communication with a wearable device worn by the user U0 or an insole sensor embedded in the user U0's shoe, and acquire detection results or measurement results from the wearable device or the insole sensor. In this case, the user terminal 100 considers the acquired detection results or measurement results as at least part of the participant's state information.

[0026] FIG. 4 is a block diagram showing the configuration of a user terminal 100 according to the second embodiment. The user terminal 100 includes a camera 110, a storage unit 120, a memory 130, a communication unit 140, an input / output unit 150, and a control unit 160. The camera 110 is an imaging device that captures images under the control of the control unit 160. The storage unit 120 is an example of a storage device including a non-volatile memory such as a flash memory or an SSD (Solid State Drive). The storage unit 120 stores a program 121, location information 122, and personal authentication information 123. The program 121 is a computer program that implements processes including a user registration process, a process for acquiring status information of participants, a status report process, a process for displaying recommended information, and the like, which will be described later. The location information 122 is GPS (Global Positioning System) information or the like, and is information indicating the current location of the user terminal 100. The personal authentication information 123 is identification information for identifying a user carrying the user terminal 100. The personal authentication information 123 may be biometric information, such as a facial image or facial feature information, or other personal identification information as described above.

[0027] The memory 130 is a volatile storage device such as RAM (Random Access Memory), and is a storage area for temporarily storing information when the control unit 160 is operating. The communication unit 140 is a communication interface with the network N. The communication unit 140 also communicates with GPS satellites. The input / output unit 150 includes a display device (display unit) such as a screen and an input device. The input / output unit 150 is, for example, a touch panel. The control unit 160 is a processor that controls the hardware of the user terminal 100. The control unit 160 loads the program 121 from the storage unit 120 into the memory 130 and executes it. In this way, the control unit 160 realizes the functions of a registration unit 161, an acquisition unit 162, and a display control unit 163.

[0028] The registration unit 161 performs a user information registration process. Specifically, the registration unit 161 accepts a facial image and personal information of the user U0 input by the user U0. The registration unit 161 transmits a user information registration request including the accepted facial image and personal information to the recommendation device 300 via the network N. Note that the registration unit 161 may include other personal authentication information for registration in place of the facial image in the registration request. The registration unit 161 may receive a user ID issued when the user information was registered from the recommendation device 300 via the network N, and register the user ID in the storage unit 120 as personal authentication information 123.

[0029] Furthermore, the registration unit 161 performs a status report process. Specifically, the registration unit 161 transmits a status report including status information, a current location, and a facial image (personal authentication information) acquired by the acquisition unit 162 as described below to the recommendation device 300 via the network N at any timing. Note that the registration unit 161 may include other personal authentication information for authentication purposes in the status report instead of a facial image. In other words, the registration unit 161 does not necessarily need to transmit a facial image every time it reports a status. Note that the registration unit 161 may perform the status report process periodically. Note that the status report process does not necessarily need to be performed periodically. For example, the registration unit 161 may perform the status report process when a change in status is detected from previously acquired status information regarding the status information acquired by the acquisition unit 162.

[0030] In addition, the registration unit 161 may accept information (adoption / rejection result) input by the participant indicating whether or not the recommendation information displayed on the display control unit 163 described later is accepted, and transmit the adoption / rejection result to the recommendation device 300 via the network N.

[0031] The acquisition unit 162 performs an acquisition process for the user's status information. The status information includes the user's health status, satisfaction (of events attended, recommended places to visit, etc.), preference information, behavioral information, etc. Specifically, the acquisition unit 162 acquires measurements (vital data) such as the user's body temperature, pulse rate, and heart rate as the health status. For example, the acquisition unit 162 acquires measurements from a health status measuring device. If the user terminal 100 is a wearable terminal, the health status measuring device may be built into the user terminal 100. Alternatively, the acquisition unit 162 may acquire measurements via short-range wireless communication from a wearable terminal worn by the user. The health status may also be the user's gait information detected by a detection device (insole sensor) embedded in an insole (shoe insole) worn by the user. The gait information includes information indicating the stride length, walking speed, contact angle, turning distance (toe direction, foot lift height), take-off angle, etc. For example, the acquisition unit 162 may acquire, as the health condition, a detected value of gait information from an insole sensor via short-range wireless communication. Furthermore, the acquisition unit 162 may acquire, as the health condition, an input value from the user on a health condition report screen. The input value may be, for example, health information such as body temperature, or a response to a medical question displayed on the report screen (selected values ​​or text information such as whether the user is in good or bad physical condition or the degree of fatigue). The acquisition unit 162 may periodically acquire the condition information. Periodically means, for example, once every hour or once a day, but the intervals are not limited to these. Alternatively, the acquisition unit 162 may acquire the condition information at any timing, such as a request from the user, instead of periodically.

[0032] The acquisition unit 162 may also acquire, as state information, the degree of satisfaction with an event attended or a recommended place to visit. For example, the acquisition unit 162 may acquire, as the degree of satisfaction, an input value (numerical value, level value, text information, etc.) from the user on a satisfaction level input screen. Alternatively, the acquisition unit 162 may acquire an image of the user taken by the camera 110 while participating in the event, and acquire, as the degree of satisfaction, the degree of smile or mood determined based on the analysis result of a predetermined analysis of the captured image.

[0033] The acquiring unit 162 may also acquire, as preference information, input values ​​(hobbies, cooking preferences, etc.) from the user on the input screen. The acquiring unit 162 may also acquire, as behavior information, input values ​​(places visited, purchase history, etc.) from the user on the input screen.

[0034] The acquisition unit 162 also acquires GPS information indicating the current location of the user terminal 100 as location information via the communication unit 140, and stores the acquired information in the storage unit 120 as location information 122. The acquisition unit 162 may also acquire an image of the user taken by the camera 110 while participating in an event, and store the image in the storage unit 120 as personal identification information 123.

[0035] When the display control unit 163 receives recommendation information from the recommendation device 300 via the network N, the display control unit 163 displays the recommendation information on the input / output unit 150.

[0036] Returning to FIG. 3, the explanation continues. The authentication device 200 is an information processing device that manages facial feature information of users. In response to a facial authentication request received from the outside, the authentication device 200 compares the facial image or facial feature information included in the request with the facial feature information of each user, and returns the comparison result (authentication result) to the request source.

[0037] FIG. 5 is a block diagram showing the configuration of an authentication device 200 according to the second embodiment. The authentication device 200 includes a face information database (DB) 210, a face detection unit 220, a feature point extraction unit 230, a registration unit 240, and an authentication unit 250. The face information DB 210 stores a user ID 211 and facial feature information 212 for the user ID in association with each other. The facial feature information 212 is a collection of feature points extracted from a facial image. The authentication device 200 may delete the facial feature information 212 from the facial feature DB 210 in response to a request from a user or the like corresponding to the facial feature information 212. Alternatively, the authentication device 200 may delete the facial feature information 212 after a certain period of time has elapsed since registration.

[0038] The face detection unit 220 detects a face region included in a registration image for registering face information, and outputs the detected region to the feature point extraction unit 230. The feature point extraction unit 230 extracts feature points from the face region detected by the face detection unit 220, and outputs face feature information to the registration unit 240. The feature point extraction unit 230 also extracts feature points included in a face image received from the recommendation device 300 or the like, and outputs the face feature information to the authentication unit 250.

[0039] The registration unit 240 issues a new user ID 211 when registering facial feature information. The registration unit 240 associates the issued user ID 211 with facial feature information 212 extracted from the registered image and registers the associated user ID 211 in the facial information DB 210. The authentication unit 250 performs facial authentication using the facial feature information 212. Specifically, the authentication unit 250 compares the facial feature information extracted from the facial image with the facial feature information 212 in the facial information DB 210. If the comparison is successful, the authentication unit 250 identifies the user ID 211 associated with the compared facial feature information 212. The authentication unit 250 returns a match of the facial feature information to the request source as a facial authentication result. The match of the facial feature information corresponds to the success or failure of authentication. Note that the facial feature information matches (matches) when the degree of match is equal to or greater than a threshold. If the facial authentication is successful, the facial authentication result includes the identified user ID.

[0040] Returning to FIG. 3, the explanation continues. The recommendation device 300 is an example of the above-mentioned recommendation device 1. The recommendation device 300 is an information processing device that performs user registration processing, status reporting processing, first recommendation processing, etc. (the recommendation method according to the second embodiment). The recommendation device 300 may be redundantly configured with multiple servers, and each functional block may be realized by multiple computers.

[0041] 6 is a block diagram showing the configuration of a recommendation device 300 according to the second embodiment. The recommendation device 300 includes a storage unit 310, a memory 320, a communication unit 330, and a control unit 340. The storage unit 310 is an example of a storage device such as a hard disk, a flash memory, or an SSD. The storage unit 310 stores a program 311 and user information 312. The program 311 is a computer program in which the processing of the recommendation method according to the second embodiment is implemented.

[0042] The user information 312 is information for managing users of the recommendation system 1000. The user information 312 is information in which a user ID 3121, personal information 3122, terminal information 3123, location information 3124, status information 3125, index value 3126, and recommendation history 3127 are associated with each other. The user ID 3121 is user identification information. The user ID 3121 is information that is identical to or uniquely corresponds to the user ID 211 that is associated with the facial feature information 212 and managed in the face information DB 210 of the authentication device 200. Therefore, the user information 312 can be said to be information associated with the user's personal authentication information for registration via the user ID 3121.

[0043] The personal information 3122 may include the user's name, sex, date of birth, address, nationality, contact information, payment information, etc. The personal information 3122 may also include the user's medical information (medical history), health information (allergy information), hobbies and preferences, etc. The personal information 3122 may also include information about the user's family.

[0044] The terminal information 3123 is information that serves as the destination of a notification to the user terminal 100 owned by the user. The terminal information 3123 is, for example, a mobile phone number, an email address, an application user ID, a social network service account, etc. The location information 3124 is information that indicates the current location of the user terminal 100 owned by the user. The location information 3124 may also be a history of location information. The status information 3125 is status information included in the above-mentioned status report. The status information 3125 may also be a history of status information.

[0045] The index value 3126 is an index value indicating the state of the user, calculated by an analysis to be described later from the state information 3125, etc. The index value 3126 can also be said to be information that quantifies the state of the user. For example, the index value 3126 is a value that indicates the user's degree of stress, the degree of pain, the severity of symptoms, etc., expressed as a numerical value, a frequency, a ratio, the presence or absence of a flag, a level, etc. The index value 3126 may also be information that indicates the user's emotion, for example, pleasant or unpleasant, the presence or absence and degree of wakefulness, the degree of sleepiness, etc.

[0046] The recommendation history 3127 is a history of recommendation information recommended to the user. The recommendation history 3127 may include the recommendation date and time, the content (event, etc.), whether the user can participate (acceptance / rejection), and the like.

[0047] The memory 320 is a volatile storage device such as a RAM (Random Access Memory), and is a storage area for temporarily storing information during operation of the control unit 340. The communication unit 330 is a communication interface with the network N.

[0048] The control unit 340 is a processor, that is, a control device, that controls each component of the recommendation device 300. The control unit 340 loads the program 311 from the storage unit 310 into the memory 320 and executes the program 311. In this way, the control unit 340 realizes the functions of an acquisition unit 341, a registration unit 342, an authentication control unit 343, a determination unit 344, and an output unit 345.

[0049] The acquisition unit 341 is an example of the acquisition unit 11 described above. In the following description, the acquisition unit 341 "acquiring" information via the network N may be expressed as the acquisition unit 341 "receiving" information. The acquisition unit 341 receives a registration request for user information from the user terminal 100. The registration request includes personal information and user authentication information (such as a facial image) for registration of the user. The acquisition unit 341 also receives a status report from the user terminal 100. The status report includes the user's status information, current location, and user authentication information (such as a facial image) for authentication. Furthermore, the acquisition unit 341 may receive an adoption / rejection result for the recommendation information from the user terminal 100.

[0050] The registration unit 342 generates user information 312 based on the received registration request and registers it in the storage unit 310. Specifically, the registration unit 342 transmits a facial information registration request including the facial image included in the registration request to the authentication device 200. Then, the registration unit 342 acquires a user ID issued in response to the registration of the facial information from the authentication device 200. Alternatively, if the authentication device 200 is not used for the personal authentication process, the registration unit 342 may issue a new user ID. The registration unit 342 generates the user information 312 by associating the issued user ID 3121 with personal information 3122 included in the registration request and terminal information 3123 of the user terminal 100 that has issued the registration request. As described above, the user ID is associated with facial feature information, and therefore the registration unit 342 can be said to associate the user's personal authentication information for registration with the personal information and register them in advance as user information.

[0051] Furthermore, the registration unit 342 updates the user information 312 by associating the location information 3124 and the status information 3125 included in the received status report with the user ID 3121 of the user authenticated by the authentication control unit 343. Furthermore, the registration unit 342 updates the user information 312 by associating the user's index value 3126, calculated by the determination unit 344 (described later), with the user ID 3121 of the relevant user. Furthermore, the registration unit 342 adds the recommendation information determined by the determination unit 344 (described later) and the result of adoption or rejection of the recommendation information to the recommendation history 3127, thereby updating the user information 312. Note that the updating of the user information 312 by the registration unit 342 may also be expressed as the registration unit 342 adding the location information 3124, the status information 3125, the index value 3126, and the recommendation history 3127 to the user information 312 initially registered in the storage unit 310 and registering them. Therefore, it can be said that the registration unit 342 registers the location information 3124 and the status information 3125 included in the received status report in association with the user ID 3121 of the user identified by the authentication control unit 343.

[0052] The authentication control unit 343 controls face authentication for the face image included in the received status report. Specifically, the authentication control unit 343 transmits a face authentication request including the face image to the authentication device 200 and receives a face authentication result from the authentication device 200. The authentication control unit 343 then determines whether authentication is successful or not based on the face authentication result received from the authentication device 200, and if authentication is successful, identifies the user ID included in the face authentication result. Note that the authentication control unit 343 may detect the user's face area from the face image and include an image of the face area in the face authentication request. Alternatively, the authentication control unit 343 may extract facial feature information from the face area and include the facial feature information in the face authentication request.

[0053] However, as described above, personal authentication is not limited to facial authentication, and the authentication control unit 343 may control authentication using personal authentication information for registration and authentication. In other words, when personal authentication information other than a facial image is included in a status report, the authentication control unit 343 controls matching with personal authentication information for registration registered in an authentication device or internally as appropriate depending on the type of personal authentication information, and performs authentication. If authentication is successful, the authentication control unit 343 identifies the corresponding user ID. Therefore, the authentication control unit 343 can be said to be an identification unit that identifies the user related to the status report by authentication using personal authentication information for registration and authentication.

[0054] The determination unit 344 is an example of the determination unit 12 described above. The determination unit 344 determines the recommendation information based on the status information of the target user. That is, the determination unit 344 determines the recommendation information at a predetermined timing using one or more pieces of status information associated with the target user. Here, the predetermined timing includes when a status report is received, i.e., when the status information is additionally registered, when a recommendation request is received from the user terminal 100 or other devices, periodically, or at any time. The determination unit 344 may also determine the recommendation information based on the status information and personal information of the target user. That is, the determination unit 344 may determine the recommendation information using at least one of the target user's health condition, such as vital data or gait information, satisfaction level with events participated in, and attribute information, such as family composition and hobbies and interests. For example, the determination unit 344 determines the recommendation information to be an invitation to participate in a first event. Furthermore, the determination unit 344 may determine the recommendation information to further include information on products or services available when participating in the first event, based on the status information.

[0055] Furthermore, the determination unit 344 may analyze the condition information to calculate an index value indicating the condition of the target user, and determine recommendation information using the index value. Specifically, the determination unit 344 performs data analysis of the target user's health condition and satisfaction level using a predetermined analysis logic, and calculates an index value that quantifies the target user's condition, such as stress or pain. The determination unit 344 may also calculate multiple index values ​​corresponding to multiple types of indicators. Furthermore, the recommendation device 300 does not necessarily need to calculate an index value when determining recommendation information.

[0056] For example, the determination unit 344 calculates a stress value, which is a numerical value representing the stress felt by the user, as an index value based on the vital data. For example, the determination unit 344 may calculate a different stress value depending on whether the pulse rate is faster or slower than a predetermined value. Furthermore, the determination unit 344 calculates a pain value, which is a numerical value representing the pain felt by the user based on gait information, as an index value. For example, the determination unit 344 may calculate a pain value by quantifying the degree of lower back pain or knee pain by comprehensively assessing the stride length, walking speed, ground contact angle, turning distance, take-off angle, etc. Furthermore, the determination unit 344 may calculate the user's emotions (such as the degree of enjoyment or boredom) as an index value based on the vital data, etc. Furthermore, the determination unit 344 may perform data analysis taking into account attribute information of the target user.

[0057] Alternatively, the determination unit 344 may calculate feature values ​​from the time-series fluctuation trends of vital data measured at multiple points in time for a specific user, and analyze the feature values ​​using a predetermined algorithm.The determination unit 344 may then calculate each index value by classifying the analysis results into multiple types of indexes.For example, the determination unit 344 may perform heart rate variability analysis from time-series heart rate data and classify the data into two types of emotion indexes, wakefulness / sleepyness and pleasantness / unpleasantness.In other words, the user's emotions may be classified into two axes, wakefulness / sleepyness and pleasantness / unpleasantness, and classified into four quadrants.

[0058] The determination unit 344 may then input the calculated index value into a recommendation model or the like to determine the recommendation information. Alternatively, the determination unit 344 may transmit a recommendation request including the calculated index value to an external server equipped with a recommendation model and receive the recommendation information from the server. Alternatively, the determination unit 344 may receive auxiliary information for determining the recommendation information, rather than the recommendation information itself, from the server and input the auxiliary information into the recommendation model or the like to determine the recommendation information. Furthermore, the determination unit 344 may transmit the recommendation request to multiple servers and collect recommendation information or auxiliary information from each server. In this case, the determination unit 344 may select part of the collected recommendation information as the recommendation information. Alternatively, the determination unit 344 may aggregate the auxiliary information to form the recommendation information. Furthermore, the determination unit 344 may determine, as the recommendation information, auxiliary information, guidance information, or advertising information of a service to be recommended to the target user. The auxiliary information may be information introducing a product or service that can be used when participating in the recommended event or using the recommended service.

[0059] The output unit 345 is an example of the above-mentioned output unit 13. The output unit 345 outputs the determined recommendation information to the user terminal 100 of the target user. The output unit 345 may also output the determined recommendation information to a terminal of a related person of the target user. Note that the output by the output unit 345 to the user terminal 100 or the like may also be expressed as the output by the output unit 345 transmitting to the user terminal 100 or the like.

[0060] Next, the user registration process, status report process, first recommendation process, etc. according to the second embodiment will be described. First, it is assumed that user U0 performs user registration using the user terminal 100 in order to receive recommendations for events suitable for the user U0 and his / her family. In this case, the user terminal 100 accepts input of a facial image and personal information of the user U0 from the user U0. For example, the user terminal 100 captures an image of the user U0's face and its surroundings using the camera 110 to acquire a facial image. Note that the user terminal 100 may accept other personal authentication information of the user U0 instead of a facial image. Furthermore, the user terminal 100 displays a personal information input screen and accepts input of personal information from the user U0. At this time, the user terminal 100 may accept the user's name, gender, date of birth, address, nationality, contact information, payment information, medical information (medical history), health information (allergy information), hobbies and preferences, family information, etc. The family information may include family composition, personal information of the family, hobbies and preferences of the family, personal authentication information of the family, etc. For example, the user terminal 100 may use an input screen for accepting such information in a selection format. Furthermore, the user terminal 100 may accept a request from the user U0 to rent a wearable device to easily obtain status information. If a user requests rental, the wearable device is delivered to the user. Thereafter, the user terminal 100 transmits a request to register user information, including the face image and personal information of the user U0, to the recommendation device 300 via the network N.

[0061] 7 is a flowchart showing the flow of user registration processing according to the second embodiment. The acquisition unit 341 of the recommendation device 300 acquires a registration request for user information from the user terminal 100 via the network N. That is, the acquisition unit 341 receives the registration request including a facial image and personal information of the user U0 (S301). Next, the registration unit 342 transmits a facial information registration request including the facial image included in the registration request to the authentication device 200 (S302).

[0062] 8 is a flowchart showing the flow of face information registration processing by the authentication device according to the second embodiment. Here, an information registration terminal (not shown) photographs the body including the face of a user, and transmits a face information registration request including the photographed image (registration image) to the authentication device 200 via the network N. The information registration terminal is, for example, an information processing device such as a personal computer, a smartphone, or a tablet terminal. For example, the information registration terminal may be a user terminal 100 or the like. Here, the information registration terminal is assumed to be the recommendation device 300 that has accepted a registration request from the user terminal 100 or the like.

[0063] First, the authentication device 200 receives a face information registration request (S201). For example, the authentication device 200 receives the face information registration request from the recommendation device 300 via the network N. Next, the face detection unit 220 detects a face area from a face image included in the face information registration request (S202). Then, the feature point extraction unit 230 extracts feature points (facial feature information) from the face area detected in step S202 (S203). Then, the registration unit 240 issues a user ID 211 (S204). Then, the registration unit 240 associates the extracted facial feature information 212 with the issued user ID 211 and registers them in the face information DB 210 (S205). Thereafter, the registration unit 240 returns the issued user ID 211 to the request source (information registration terminal, for example, the recommendation device 300) (S206).

[0064] Returning to FIG. 7, the description will be continued. The registration unit 342 of the recommendation device 300 acquires a user ID issued in response to the registration of face information from the authentication device 200 (S303). If the registration request does not include a face image or personal authentication information of the user U0, the registration unit 342 issues a new user ID as personal authentication information. The registration unit 342 identifies personal information included in the registration request and identifies terminal information of the user terminal 100 that has issued the registration request. The terminal information may be included in the registration request. Thereafter, the registration unit 342 generates user information 312 by associating the acquired or issued user ID 3121, the identified personal information 3122, and the identified terminal information 3123. Then, the registration unit 342 registers the generated user information 312 in the storage unit 310 (S304). At this time, the recommendation device 300 may transmit the acquired or issued user ID to the user terminal 100 via the network N. At this time, the user terminal 100 may store the received user ID in the storage unit 120 as personal authentication information 123.

[0065] Next, the status report process will be described. The user terminal 100 acquires status information from the user U0 at any timing using various means as described above. At this time, the user terminal 100 reads the personal authentication information 123 and the location information 122 from the storage unit 120. Then, the user terminal 100 transmits a status report including the read personal authentication information (such as a face image), location information (current location), and the acquired status information to the recommendation device 300 via the network N. The user terminal 100 may determine whether the change in status of the acquired status information is within a certain range compared with status information acquired up to that point, and transmit the status report if it exceeds the certain range. As a result, if the change in status is within the certain range, the transmission process of the status information is not performed, thereby reducing the amount of communication and the number of communications. Furthermore, the recommendation device 300 can consider the health status of a specific user to be stable while no status report is received from the user.

[0066] 9 is a flowchart showing the flow of the status report process according to the present embodiment 2. First, the acquisition unit 341 of the recommendation device 300 receives a status report from the user terminal 100 via the network N (S311). Here, the status report includes personal authentication information, location information (current location), and status information.

[0067] Next, the authentication control unit 343 identifies the user by authenticating the personal authentication information included in the received status report (S312). Specifically, the authentication control unit 343 controls matching of the personal authentication information for authentication included in the status report with pre-registered personal authentication information to perform authentication. The authentication control unit 343 identifies the user by the user ID associated with the registration personal authentication information that has been successfully authenticated.

[0068] The following describes an example in which the personal authentication is face authentication. In this case, the authentication control unit 343 transmits a face authentication request including the face image included in the received status report to the authentication device 200 via the network N. In response to this, the authentication device 200 performs face authentication processing.

[0069] FIG. 10 is a flowchart showing the flow of face authentication processing by the authentication device according to the second embodiment. First, the authentication device 200 receives a face authentication request from the recommendation device 300 via the network N (S211). The authentication device 200 may also receive a face authentication request from the user terminal 100 or the like. Next, the authentication device 200 extracts facial feature information from the face image included in the face authentication request, similar to steps S202 and S203 described above. Then, the authentication unit 250 of the authentication device 200 compares the facial feature information extracted from the face image included in the face authentication request with the facial feature information 212 in the face information DB 210 (S212) and calculates the degree of match. Then, the authentication unit 250 determines whether the degree of match is equal to or greater than a threshold (S213). If the facial feature information matches, that is, if the degree of match of the facial feature information is equal to or greater than the threshold, the authentication unit 250 identifies the user ID 211 associated with the facial feature information 212 (S214). Then, the authentication unit 250 returns the face authentication result, including the fact that the face authentication was successful and the identified user ID 211, to the recommendation device 300 via the network N (S215). If the degree of match is less than the threshold in step S213, the authentication unit 250 returns the face authentication result, including the fact that the face authentication was unsuccessful, to the recommendation device 300 via the network N (S216).

[0070] Returning to FIG. 10, the explanation will be continued. The authentication control unit 343 of the recommendation device 300 receives the face authentication result from the authentication device 200 via the network N. Then, the authentication control unit 343 determines whether or not face authentication has been successful based on the received face authentication result. If it is determined that face authentication has been successful, the authentication control unit 343 identifies a user ID included in the face authentication result and identifies the user ID as the user. On the other hand, if face authentication has failed, the recommendation device 300 may return a message to that effect to the user terminal 100.

[0071] Here, the description will continue assuming that the face authentication was successful. At this time, the registration unit 342 registers the current location and status information included in the status report in the user information 312 of the identified user (S313). Specifically, the registration unit 342 acquires the current location and status information included in the status report, and updates the participant information 312 by associating the location information 3124 and status information 3125 with the user ID 3121 whose face authentication was successful.

[0072] 11 is a flowchart showing the flow of the first recommendation process according to the second embodiment. The recommendation device 300 performs the first recommendation process at a predetermined timing. The predetermined timing is, for example, periodically after executing a status report process, or when the recommendation device 300 receives a recommendation request from the user terminal 100. For example, the user terminal 100 accepts a recommendation request for an experiential event based on registered user information from the user U0, and transmits the recommendation request including personal authentication information to the recommendation device 300 via the network N.

[0073] First, the determination unit 344 of the recommendation device 300 selects a target user at a predetermined timing (S321). For example, the determination unit 344 selects a user ID included in any user information from the plurality of pieces of user information 312. Alternatively, the determination unit 344 selects a user ID for which a status report is registered as the target user. Alternatively, the determination unit 344 selects a user ID corresponding to personal authentication information included in the recommendation request as the target user.

[0074] Next, the determining unit 344 identifies the status information 3125 and personal information 3122 of the target user from the user information 312 (S332). Then, as described above, the determining unit 344 analyzes the identified status information 3125 and personal information 3122 to calculate an index value indicating the status of the target user (S333). At this time, the registering unit 342 may register the calculated index value 3126 in the user information 312 in association with the selected user ID 3121.

[0075] Then, the determination unit 344 determines the recommendation information using the calculated index value as described above (S334). Specific examples of steps S333 and S334 will be described later.

[0076] Thereafter, the output unit 345 outputs the determined recommendation information to the user terminal 100 of the target user (S335). Specifically, the output unit 345 identifies the terminal information 3123 associated with the user ID 3121 of the target user from the user information 312. Then, the output unit 345 transmits the determined recommendation information to the identified terminal information as the destination. In response to this, the user terminal 100 displays the received recommendation information as a recommendation screen on the input / output unit 150.

[0077] 12 is a diagram showing an example of the display of recommendation information according to the second embodiment. Here, an example is shown in which the user terminal 100 displays a recommendation screen 51 including guidance information to a participatory event as recommendation information. The recommendation screen 51 for a participatory event includes recommendation information 511 and an application to participate button 512. The recommendation information 511 is an example that shows, for example, the name of the recommended participatory event, the date and time of the event, a description, the target age (participation conditions), and the location of the event. When the application to participate button 512 is pressed, a screen for inputting or selecting the names of participants is displayed.

[0078] When the user terminal 100 accepts the input or selection of a participant name, it transmits a participation application request including a list of participant names, a user ID (personal authentication information), an event ID, etc. to the recommendation device 300 via the network N. The recommendation device 300 performs application processing for the relevant event based on the information included in the received participation application request. If the applied-for event requires a fee, the recommendation device 300 settles the usage fee using the payment information included in the personal information 3122 associated with the user ID 3121. Thereafter, user U1 can go to the participatory event venue with his / her family and participate in the event.

[0079] Here, a method for determining recommended information for a user and specific examples of recommended information will be described. For example, the recommendation device 300 may recommend (provide information to) the user recommendation information determined based on the stress value and pain value calculated as the index value in step S333. For example, if the stress value is higher than a predetermined value, the recommendation device 300 may determine recommended information related to places, events, etc. where the user can relax. Furthermore, if the pain value related to lower back pain calculated from gait information, etc. is higher than a predetermined value, the recommendation device 300 may determine, as recommended information, information on hospitals, facilities, etc. that can provide walking instruction to the user who has lower back pain. Furthermore, the recommendation device 300 may determine the user's health condition based on the stress value and pain value, and recommend recommended information determined based on the determination result to the user. For example, if the stress value and lower back pain are lower than predetermined values, the recommendation device 300 determines the user's health condition as "excellent." On the other hand, if the stress value is higher than a predetermined value and the user has lower back pain, the recommendation device 300 determines the user's health condition as "poor." Then, the recommendation device 300 may provide health-related information to a user whose health condition is determined to be "poor."

[0080] Furthermore, the recommendation device 300 may calculate the severity of lifestyle-related disease symptoms as an index value from condition information such as vital data and medical information (medical history) included in the personal information, and determine information for alleviating the symptoms as recommendation information. Furthermore, if the user is elderly, the recommendation device 300 may calculate an index value of the user's health condition from condition information, medical information, and the like, and determine different health advice for relatively healthy elderly people of the same generation and other elderly people as recommendation information. These can contribute to improving the user's health.

[0081] Furthermore, the recommendation device 300 may determine, as the recommendation information, guidance information regarding products for sale, services provided, participatory events, and the like, based on the status information and the hobbies, preferences, and family information included in the personal information. For example, the recommendation device 300 may determine, as the recommendation information, an outdoor experience as a participatory event. In this case, the operator of the recommendation device 300 may collaborate with an outdoor manufacturer to rent equipment (tents, etc.) required for the event experience. In other words, when recommending a participatory event, the recommendation device 300 may also include, in the recommendation information, information introducing rental of equipment, etc., that can be used at the event. This allows the user to easily apply for equipment rental when applying to participate in the event, and makes it easier for the user to decide whether to purchase the rented equipment, etc., after the event experience. This can contribute to increased sales for outdoor manufacturers.

[0082] Furthermore, the operator of the recommendation device 300 may cooperate with a local government or the like in a specific region to provide information about the region. For example, the cooperating local government may have tourist resources such as the sea, mountains, and rivers. In this case, the recommendation device 300 selects users who live near the specific region as target users based on addresses included in the personal information 3122 in the user information 312. Then, the recommendation device 300 may determine exercise experiences, meals, and the like in the region as recommendation information based on the status information and personal information (hobbies, preferences, family information) of the target users. This can contribute to revitalizing the region.

[0083] Furthermore, the recommendation device 300 may determine local government services as recommendation information for residents, commuters, students, etc. in a specific area. In this case, the recommendation device 300 selects a target user based on information such as address, workplace, and school included in the personal information 3122 in the user information 312. Then, the recommendation device 300 may determine, as recommendation information, a guide to taking a health checkup to be conducted in the area based on the condition information and index values ​​related to the health condition of the target user. Note that the method of determining recommendation information and specific examples of recommendation information are not limited to those described above.

[0084] In this way, the recommendation device 300 according to this embodiment calculates index values ​​that quantify various indicators indicating the user's state by analyzing data using periodically registered user state information and pre-registered personal information, etc. The recommendation device 300 determines recommendation information using the index values ​​and provides the information to the user. Therefore, it is possible to recommend appropriate information according to the user's state.

[0085] <Embodiment 3> The third embodiment is a modification of the second embodiment. The recommendation device 300a according to the third embodiment acquires the user's impressions of the user's experience based on the recommendation information, changes in the user's health condition in response to the experience, and the like. That is, the recommendation device 300a may receive feedback from the user regarding the user's experience based on the recommendation information. For example, the recommendation device 300a may acquire changes in the user's emotions resulting from the user's actual participation in a recommended event, etc., and use the acquired information to help determine further recommendation information.

[0086] FIG. 13 is a block diagram showing the overall configuration of a recommendation system 2000 according to the third embodiment. In the following description, components similar to those in the second embodiment are denoted by the same reference numerals, and illustrations and detailed descriptions thereof are omitted. The recommendation system 2000 is a system in which the recommendation device 300 described above is replaced with a recommendation device 300a. The recommendation system 2000 indicates that a user U0 possessing a user terminal 100 participated in a first event held at an event venue 40. Here, the first event may be an event involving the participant's experience, or an event such as appreciation. For example, the first event may be an event recommended to the user U0 according to the second embodiment and attended by the user U0 based on the recommendation information. Alternatively, the first event may be an event in which the user U0 participated voluntarily, without being recommended.

[0087] The recommendation device 300a is an improved version of the recommendation device 300 described above, and provides recommendation information to the user U0 by taking into account status information of the user U0 before and after participating in an event. Specifically, the acquisition unit of the recommendation device 300a acquires first status information of the user U0 before participating in a first event and second status information of the user after participating in the first event. Furthermore, the determination unit of the recommendation device 300a derives a change in the status of the user U0 from the first status information to the second status information, and determines recommendation information based on the derived status change. Here, the recommendation information may be guidance information for the second event, or may be any of the above-mentioned various recommendation information other than events. The recommendation information may take into account at least the change in status of the user U0 due to his / her participation in the event.

[0088] 14 is a flowchart showing the flow of the second recommendation process according to the third embodiment. It is assumed that the above-described user registration process and the status report process before participating in the first event have been completed for user U0. However, it does not matter whether user U0 has been recommended for the first event held at the event venue 40 by the above-described first recommendation process. It is assumed that user U0 has at least participated in the first event held at the event venue 40.

[0089] First, the recommendation device 300a performs a registration process for a status report of user U0 after participating in the first event (S320). Specifically, after user U0 participates in the first event at the event venue 40, the user terminal 100 acquires status information from user U0 by various means as described above. Then, as described above, the user terminal 100 transmits a status report including user U0's personal authentication information, location information of the event venue 40, and status information after participating in the first event to the recommendation device 300a via the network N. Identification information of the first event may be used instead of the location information of the event venue 40. In response to this, the recommendation device 300a performs a registration process for the status report in the same manner as in FIG. 9 described above. That is, the user information 312 of user U0 includes first status information before participating in the first event and second status information after participating in the first event.

[0090] Next, the recommendation device 300a selects user U0 who participated in the first event as a target user (S321a). For example, the recommendation device 300a identifies the event venue 40 from the location information included in the status report received in step S320, and identifies the first event from the event schedule (not shown) at the event venue 40 and the acquisition time of the status information included in the status report. Then, the recommendation device 300a may select user U0 from a participant list (not shown) of the identified first event.

[0091] Then, the recommendation device 300a identifies the state information 3125 and personal information 3122 of the target user before and after participating in the event from the user information 312 (S332a). Subsequently, the recommendation device 300a analyzes the state information 3125 and personal information 3122 before and after participating in the event to calculate index values ​​indicating the state of the target user before and after participation (S333a). That is, the recommendation device 300a calculates a first index value before participating in the first event and a second index value after participating in the first event.

[0092] Then, the recommendation device 300a outputs the index values ​​before and after participation to the user terminal 100 of the target user (S335a). In response to this, the user terminal 100 displays the received index values ​​before and after participation on the input / output unit 150.

[0093] FIG. 15 is a diagram showing an example of displaying index values ​​before and after participation according to the third embodiment. Here, an example is shown in which the user terminal 100 displays a status change summary screen 52 before and after participating in an event. The status change summary screen 52 includes status changes 521 and 522. The status change 521 is an example of displaying a comparison of multiple indexes between the daily average value of user U0 before participating in the first event and the average value on the day of participating in the first event. For example, the first index is calories burned, which indicates a change (increase) from "2,500 kcal" before participation to "5,000 kcal" after participation. The second index is the number of steps, which indicates a change (increase) from "2,000 steps" before participation to "15,560 steps" after participation. The third index is stress level, which includes anxiety level, tension level, and friendliness level. The anxiety level indicates a change (decrease) from "5" before participation to "3" after participation. The tension level indicates a change (decrease) from "4" before participation to "2" after participation. The friendship level indicates a change (increase) from "3" before participation to "4" after participation. The status change 522 is a comparison of the hourly change in the total stress level (total stress level) of multiple indicators before and after participation, displayed in a graph. The higher the anxiety and tension levels, the higher the total stress level, and the lower the friendship level, the higher the total stress level. In the status change 522, the average value (solid line) on the day of participation in the first event is lower than the daily average value (dashed line) before participation in the first event, indicating that user U0's stress level decreased due to participation in the event. If the recommendation device 300 detects a time or time period in which the change in stress value in the transition of the total stress level is greater than a predetermined value, the user terminal 100 may display, on the status change summary screen 52, events, etc., that the user participated in during the detected time period.

[0094] Returning to FIG. 14, the description will be continued. Independently of step S335a, after step S333a, the recommendation device 300a determines recommendation information based on the index values ​​before and after participation in the event (S334a). Then, the recommendation device 300a outputs the determined recommendation information to the user terminal 100 of the target user (S335). In response to this, the user terminal 100 displays the received recommendation information as a recommendation screen on the input / output unit 150.

[0095] FIG. 16 is a diagram showing an example of the display of recommendation information according to the third embodiment. Here, an example is shown in which the user terminal 100 displays a recommendation screen 53 including guidance information for a second participatory event as recommendation information. The recommendation screen 53 for the second participatory event includes recommendation information 531 and an application to participate button 532. The recommendation information 531 is an example that indicates, for example, the name of the recommended participatory event, the date and time of the event, a description, the target age (participation conditions), and the location of the event. Here, it is assumed that an event more suitable for user U0 has been determined as the recommendation information based on the change in user U0's status (change in index value) before and after participating in the first event. When the application to participate button 532 is pressed, a screen for inputting or selecting a participant name is displayed. As described above, user U0 can apply for and participate in the recommended event.

[0096] Here, a specific example of recommending a second event based on the first event and the change in the user's state after the experience will be described. For example, if the stress value of user U0 (before participating in the first event) is higher than a predetermined value, the recommendation device 300a determines and recommends a relocation "experience" (first event) of a resort or the like as recommendation information in a first recommendation process. Then, the recommendation device 300a acquires state information after the relocation experience from user U0. The state information after the relocation experience (after participating in the event) includes vital data, etc., and the user's impressions of the relocation experience (satisfied or dissatisfied), etc. If the user U0's impressions after the relocation experience are satisfactory, or if the degree of stress value reduction (state change) calculated from vital data, etc. before and after the relocation experience is good, the recommendation device 300a may determine and recommend "permanent residence" in the resort as the next recommendation information.

[0097] Alternatively, the recommendation device 300a may determine recommendation information based on personal information of the user U0 (e.g., hometown or hobbies and interests). For example, if the user U0 is from a rural area or likes nature, the recommendation device 300a determines and recommends an experience in an area rich in nature (e.g., mountain climbing, a first event). At this time, the recommendation device 300a may adjust the level of difficulty of the mountain climbing by taking into account the user's health condition. The recommendation device 300a then acquires post-mountain climbing status information from the user U0. If the user U0's impression after climbing is satisfactory, or if their health condition, such as vital data before and after climbing, is good, the recommendation device 300a may determine and recommend climbing another mountain as the next recommendation information. On the other hand, if the user U0's impression after climbing is dissatisfied, the recommendation device 300a may determine and recommend another experience for people who like nature, such as an experience related to a river or the sea, as the next recommendation information. Furthermore, if the health condition or stress level of the user U0, such as vital data before and after mountain climbing, is not good, the recommendation device 300a may determine and recommend mountain climbing with a lower level of difficulty as the next recommendation information.

[0098] In this way, in the third embodiment, status information after experiencing a recommended event (activity, etc.), such as health status and interests, is recorded (feedback). Then, a new recommendation is made including the most suitable experiential event (experiential learning, etc.) based on the feedback. The recommendation information may also include a medical checkup at a medical institution. In this case, the medical checkup results are included in the status information after the experience. In other words, the most suitable medical checkup can be further recommended depending on the accumulation of medical checkup results, etc.

[0099] <Embodiment 4> The fourth embodiment is a modification of the second embodiment described above. The fourth embodiment grasps the user's emotions and emotional changes in real time, and determines and provides information to be recommended according to the grasped content. In particular, the recommendation device 300b according to the fourth embodiment may change the production content of an event currently being held according to the emotions and emotional changes of users participating in the event.

[0100] FIG. 17 is a block diagram showing the overall configuration of a recommendation system 3000 according to the fourth embodiment. In the following description, components similar to those in the second embodiment are denoted by the same reference numerals, and illustrations and detailed descriptions thereof are omitted. In the recommendation system 3000, the recommendation device 300 described above is replaced with a recommendation device 300b, and an event organizer device 500 is added. A second event is being held at the event venue 40. The second event may be, for example, a concert, a play, or a theme park attraction. The second event is being produced by the organizer, i.e., staff U5 and devices on the organizer's side. Users U1 to U4 are participating in the second event. User U1 owns a user terminal 100-1, user U2 owns a user terminal 100-2, user U3 owns a user terminal 100-3, and user U4 owns a user terminal 100-4. The user terminals 100-1 to 100-4 have functions equivalent to those of the user terminal 100 described above.

[0101] The event organizer device 500 is an example of a device on the organizer side of the event described above, and is connected to the network N. The event organizer device 500 is, for example, an information processing device such as a personal computer, a mobile phone terminal, a smartphone, or a tablet terminal. The event organizer device 500 receives recommendation information from the recommendation device 300b via the network N and displays it on a screen. This allows the staff member U5 to visually recognize the recommendation information via the recommendation device 300b. The recommendation information may be, for example, information about the production content of the second event, or the distribution of user emotions by area within the venue of the second event.

[0102] Alternatively, the event organizer's device 500 may have a function as a performance control device that controls performance devices (for example, speakers, lighting equipment, projectors, etc.) in the event venue 40.

[0103] An acquisition unit of the recommendation device 300b acquires status information from at least one of users U1 to U4 participating in the second event. A determination unit of the recommendation device 300b determines recommendation information based on the time or place at which the status information was acquired from the user and the status information. An output unit of the recommendation device 300b outputs the determined recommendation information to an apparatus (event organizer apparatus 500) on the organizer side of the second event as an output destination. This allows staff U5 on the organizer side of the event to understand the status (level of excitement, satisfaction), emotions, etc. of the participants of the second event. Note that the output unit of the recommendation device 300b may output the determined recommendation information to any one of user terminals 100-1 to 100-4 from which the status information was acquired as an output destination.

[0104] Furthermore, the determination unit of the recommendation device 300b may determine information related to the production content of the second event as the recommendation information. This allows staff U5 to propose changes to the production content in real time according to the emotions of the participants of the second event, etc. The determination unit may also include the reason for changing the production content in the recommendation information. For example, the reason for changing the production content may be that many enthusiastic users are adding a production that uses lighting. The determination unit may also include the production content before and after the change in the recommendation information. This allows staff U5 to understand the reason for changing the proposed production content and the production content before and after the change.

[0105] Furthermore, the output unit of the recommendation device 300b outputs an instruction to apply the rendering content of the second event. This allows the event organizer device 500 to apply the rendering content of the second event to the rendering device described above. Therefore, the rendering content of the second event can be changed in real time according to the emotions of the participants, etc.

[0106] Furthermore, the acquisition unit of the recommendation device 300b may acquire state information at multiple points in time from users participating in the second event. In this case, the determination unit may derive changes in the user's state from the state information at each point in time and determine recommendation information based on the derived state changes. This allows for more effective presentation in response to changes in the participants' emotions as the second event progresses, thereby improving participant satisfaction.

[0107] 18 is a flowchart showing the flow of the third recommendation process according to the fourth embodiment. It is assumed that the above-described user registration process and the status report process before participating in the second event have been completed for each of users U1 to U4. However, it does not matter whether or not the first recommendation process has resulted in a recommendation for the second event held at the event venue 40. It is assumed that each of users U1 to U4 is currently participating in at least the second event held at the event venue 40.

[0108] First, the recommendation device 300b performs a registration process of status reports at multiple time points during participation in the second event (S320b). Specifically, while user U1 is participating in the second event being held at the event venue 40, the user terminal 100-1 acquires status information at multiple time points from user U1 by various means as described above. Then, as described above, the user terminal 100-1 transmits a status report including user U1's personal authentication information, location information of the event venue 40, and status information at multiple time points during participation in the second event to the recommendation device 300b via the network N. Identification information of the second event may be used instead of the location information of the event venue 40. In response to this, the recommendation device 300b performs a registration process of multiple status reports, similar to that described in FIG. 9. That is, the user information 312 of user U1 includes status information at multiple time points during participation in the second event.

[0109] Next, the recommendation device 300b selects user U1, who is participating in the second event, as a target user (S321b). For example, the recommendation device 300b identifies the event venue 40 from the location information included in the status report received in step S320b, and identifies the second event from the event schedule (not shown) at the event venue 40 and the acquisition time of the status information included in the status report. Then, the recommendation device 300b may select user U1 from a participant list (not shown) of the identified second event.

[0110] Then, the recommendation device 300b identifies the state information 3125 and personal information 3122 of the target user at each time point while participating in the event from the user information 312 (S332b). Next, the recommendation device 300b analyzes the state information 3125 and personal information 3122 at each time point while participating in the event to derive changes in the state of the target user while participating in the event (S333b). For example, the recommendation device 300b detects whether the user U1 is excited or scared (by the effects of the attraction) based on changes in the heart rate, stress value, etc. during the second event.

[0111] The recommendation device 300b then determines recommendation information (event performance) based on the derived change in state (S334b). The recommendation device 300b then outputs the determined recommendation information to the event organizer device 500 (S335b). In response, the event organizer device 500 displays the received recommendation information on the input / output unit 150. The staff member U5 can then determine and implement (instruct) a change in performance depending on the change in user U1's emotion. Specifically, different performances may be performed depending on whether user U1's heart rate increases or decreases at a certain point in the event. For example, if the event is a horror event and it is detected that user U1's heart rate is not sufficiently increased (is not scared), a performance in which a ghost appears may be performed. At this time, the event organizer device 500 may instruct the performance device to apply the change in performance.

[0112] Furthermore, the acquisition unit of the recommendation device 300b may acquire status information and location information of each user for multiple users participating in the second event. In this case, the determination unit analyzes the emotions of each user from the status information and determines, as recommendation information, the emotion distribution of users for each area within the venue of the second event based on the emotions and location information. Then, the output unit transmits the emotion distribution to the event organizer device 500. As a result, the event organizer device 500 displays the emotion distribution of users for each area within the event venue 40 (emotion map). Therefore, the staff member U5 can perform appropriate performances for each area based on the emotion map. Furthermore, the output unit may transmit the emotion distribution to the user terminal. That is, the recommendation device 300b may disclose the emotion distribution to the user. As a result, the user terminal displays the emotion distribution of users for each area within the event venue 40 on a screen. Therefore, the user can confirm their preferred area within the event venue 40, such as an active area or a calm area, and then head to that area. The output unit may also transmit the emotion distribution and other recommendation information to a user who intends to join the second event midway or to a user terminal of a user who is outside the event venue 40.

[0113] Furthermore, the determination unit of the recommendation device 300b may further determine the location to which the effect content is to be applied based on the emotion distribution. In this case, the output unit specifies the application location and outputs an instruction to apply the effect content for the event. This makes it possible to automatically perform appropriate effects for each area according to the emotion map.

[0114] 19 is a flowchart showing the flow of the fourth recommendation process according to the fourth embodiment. The premise is the same as that of FIG.

[0115] First, the recommendation device 300b performs a registration process of status reports of multiple users participating in the second event (S320c). Specifically, while users U1 to U4 are participating in the second event being held at the event venue 40, each of the user terminals 100-1 to 100-4 acquires status information from each of the users U1 to U4 by various means as described above. Then, as described above, each user terminal transmits a status report including each user's personal authentication information, location information of the event venue 40, and status information during participation in the second event to the recommendation device 300b via the network N. Identification information of the second event may be used instead of the location information of the event venue 40. In response to this, the recommendation device 300b performs a registration process of each user's status report, similar to the above-described FIG. 9. That is, the user information 312 of each user includes status information during participation in the second event.

[0116] Next, the recommendation device 300b selects users U1 to U4 who are participating in the second event as target users (S321c). For example, the recommendation device 300b identifies the event venue 40 from the location information included in the status report received in step S320c, and identifies the second event from the event schedule (not shown) at the event venue 40 and the acquisition time of the status information included in the status report. Then, the recommendation device 300b may select users U1 to U4 from a participant list (not shown) of the identified second event.

[0117] The recommendation device 300b then identifies the status information 3125 and personal information 3122 of the target user group during event participation from the user information 312 (S332c). Subsequently, the recommendation device 300b analyzes the status information 3125 and personal information 3122 during event participation to derive the emotion of each user participating in the event (S333c). The recommendation device 300b then determines recommendation information (emotion distribution) for each area within the event venue based on the derived emotion and the location information of each user (S334c). Specifically, the recommendation device 300b aggregates the emotions (analysis results) of a group of users with similar location information to identify the emotion in each area. For example, the recommendation device 300b calculates an average value of the analysis results of the emotions of multiple users staying in each area for each of multiple areas within the event venue 40, and identifies the emotion in the area corresponding to the average value. Similarly, the recommendation device 300b labels the identified emotion to the corresponding area to generate an emotion distribution.

[0118] Then, the recommendation device 300b outputs the determined recommendation information (emotion distribution) to the event organizer device 500 (S335c). In response to this, the event organizer device 500 displays the received recommendation information on the input / output unit 150.

[0119] 20 is a diagram showing a display example of an emotion distribution 400 according to the fourth embodiment. The emotion distribution 400 shows the analysis results of emotions of a group of users in each of multiple areas 41 to 46 in an event venue 40. For example, area 41 shows "extreme enthusiasm," area 42 shows "excitement," area 43 shows "tension," area 44 shows "joy," area 45 shows "excitement," and area 46 shows "depression." However, the emotion analysis results are not limited to these.

[0120] Thereafter, the staff member U5 checks the emotion distribution 400 and can decide to change or implement (instruct) a change in the performance in response to changes in the emotion of the user U1. For example, the staff member U5 can visually grasp, using the emotion distribution 400, areas where the event participants are excited, areas where they are not excited, or areas where they are relaxed. Therefore, for example, during a concert, which is the second event, if there are many users who are not enthusiastic in a certain area, the performance using lighting or the like may be changed in that area. Furthermore, a performance such as fireworks may be applied near an area where people are excited (enthusiastic). Alternatively, a performance designed to relax people in an excited area may be applied. In these cases, the event organizer device 500 may instruct the performance device to apply the change in the performance.

[0121] Furthermore, the recommendation device 300b may output the emotion distribution to the user terminal. For example, if it is desirable to keep the heart rate within a predetermined value in consideration of the user's health condition, the recommendation device 300b may recommend that the user move to an area in the event venue 40 where the user can relax. Furthermore, the recommendation device 300b may make a recommendation again or change the content of the presentation using the user's state information after the recommendation.

[0122] 18 and S332c in Fig. 19, the recommendation device 300b does not necessarily need to identify personal information of the user participating in the event. In this case, in S332b and S332c, the recommendation device 300b analyzes the state of the target user at each point in time while the target user is participating in the event, and derives changes in the state and emotions of the target user while participating in the event.

[0123] Furthermore, the recommendation device 300b may determine recommendation information in response to a recommendation request from a user terminal and output the recommendation information to the user terminal. That is, the user may be able to check, on the user terminal, the above-described emotion distribution, the change in the presentation, the reason for the change in the presentation, and the presentation before and after the change.

[0124] Here, the emotion distribution in FIG. 20 described above is an example showing the distribution of emotions of each participant at an event venue at a certain time on a two-dimensional map. Alternatively, the recommendation device 300b may output, during the event, changes in the emotion distribution over time to the event organizer device 500 or the user terminals of users participating in the event. For example, the recommendation device 300b generates display information (e.g., a pie chart) showing the ratio of the number of users in the event venue as the emotion distribution. The recommendation device 300b then stores the generated display information in the storage unit 310 or the memory 320 in association with the acquisition time of the state information. With two or more pieces of display information stored, the recommendation device 300b then outputs the display information so as to display changes in the emotion distribution (display information) over time.

[0125] For example, assume that there are no changes to the production content until 10 minutes after the start of an event, and an increasing number of participants express boredom. In this case, the recommendation device 300b determines the changes to the production content, the reason for the change, the application location, etc., based on the emotion distribution 10 minutes after the start of the event. Then, the recommendation device 300b specifies the application location and outputs an instruction to apply the production content of the event. For example, the recommendation device 300b determines that the production content at the event venue before the change, which was only lighting, should be changed to fireworks to increase the excitement level of the participants. In this case, the recommendation device 300b may specify an area where more users are determined to be bored as the application location. The recommendation device 300b generates an emotion distribution according to status reports acquired and registered after the change to the production content (for example, 20 minutes after the start of the event). Then, the recommendation device 300b displays the changes in the generated emotion distributions along a time series.

[0126] FIG. 21 is a diagram showing an example of changes in emotion distribution over time according to the fourth embodiment. The emotion distribution over time 401 shows the changes over time in the emotion distribution of each user in the entire venue or in a specific area. The emotion distribution over time 401 also shows the temporal change in emotion distribution from left to right. Specifically, the emotion distribution over time 401 is an example of displaying an emotion distribution 410 at the start of an event, an emotion distribution 420 10 minutes after the start of the event, and an emotion distribution 430 20 minutes after the start of the event. The emotion distribution 410 shows that excitement 411, joy 412, and tension 413 are roughly evenly distributed among each user at the start of the event due to expectations for the event, and there is little pessimistic emotion. Here, it is assumed that there were no changes to the performance content until 10 minutes after the start of the event. Emotion distribution 420 is the emotion distribution 10 minutes after the start of the event. Compared to emotion distribution 410, it shows that excitement 421 and joy 422 have decreased, tension 423 has remained roughly the same, and boredom 424 has been added in a large proportion. Pre-change performance content 441 is text information indicating that the performance content was "lighting" 10 minutes after the start of the event. Emotion distribution 430 is the emotion distribution 20 minutes after the start of the event, i.e., after the above-mentioned performance content change. Compared to emotion distribution 420, emotion distribution 430 shows that a large proportion of enthusiasm 431 has been added, excitement 432 and joy 433 have increased, and tension 434 and boredom 435 have decreased. Pre-change performance content 442 is text information indicating that the performance content has been changed to "fireworks" 20 minutes after the start of the event. Reason for change 443 is text information indicating the reason for changing from pre-change performance content 441 to post-change performance content 442. Here, the reason for change 443 indicates information such as "Because the excitement level of many users in the area was low." The reason for change may also be "Because the excitement level of many users in the area was high, in order to make them even more excited" (the performance content was changed to launch fireworks). Furthermore, the emotion distribution over time 401 may be displayed on the event organizer device 500 or another computer not only during the event but also after the event. The emotion distribution over time 401 may be displayed corresponding to each of the above-mentioned areas 41 to 46.In this case, the emotion distribution may be displayed so that it is easy to compare each area. The emotion distribution for each area may also be displayed so that it is easy to compare them over time. The emotion distribution may also be a distribution of average emotions corresponding to each of the areas 41 to 46. That is, the average emotion analysis results of the emotions of multiple users staying in each area may be displayed at a location corresponding to each area in the emotion distribution. In this case, the emotion distribution may be assigned a display size such as excitement 411 in proportion to the number of people staying in each area. The user terminal may then display the emotion distribution for each area and its time progression. This allows, for example, a user to check the changes in the emotion distribution for each area displayed on their user terminal and use this as a cue to move to a desired area during an event.

[0127] 22 is a diagram showing an example of the display of the performance content before and after the change and the reason for the change according to the fourth embodiment. Here, it is assumed that the change in the performance content (launching fireworks) described above was carried out near the front left of the area of ​​the event venue 40. It is also assumed that a recommendation screen 54 was displayed on the user terminal 100-1 carried by a user U1 who was near the front left of the area of ​​the event venue 40. The recommendation screen 54 includes performance content before and after the change 541 and a reason for the change 542. The performance content before and after the change 541 includes the performance content before the change 441 and the changed performance content 442 described above. The reason for the change 542 is the same as the reason for the change 443 described above.

[0128] Fig. 23 is a diagram showing a display example of an emotion distribution 400a according to embodiment 4. The emotion distribution 400a is obtained by adding, to the emotion distribution 400 in Fig. 20 described above, an application location 47 of the effect change, effect contents before and after the change 541, and a reason for the change 542.

[0129] Furthermore, the recommendation device 300b may utilize the results of the above-described emotion analysis (emotion distribution, etc.) for product sales, etc. For example, the recommendation device 300b may specify an area where there is enthusiasm and instruct a van for product sales, etc. to be sent there. This can contribute to promoting sales of products to enthusiastic participants.

[0130] The recommendation device 300b may also analyze information on changes in emotions and provide the analysis results to the event organizer device 500. The analysis results may include timings and locations (areas) in the event program where participants were excited or relaxed. This allows the event organizer to utilize the analysis results in future events that they plan. The recommendation device 300b may also provide information to users by posting the analysis results, emotion distribution, and the like to an SNS (Social Networking Service) server.

[0131] <Other embodiments> The user may be a tourist visiting a tourist spot. In this case, the recommendation device 300, 300a, or 300b (hereinafter, referred to as the recommendation device 300, etc.) may calculate the tourist's level of interest in the tourist spot as an index value from status information acquired from the tourist's user terminal, and provide information according to the level of interest as recommendation information. For example, if the tourist is highly interested in a tourist resource such as a castle, the recommendation device 300, etc. may provide more in-depth information about the castle, or if the tourist is not highly interested, may guide the tourist to change to another tourist resource. The recommendation device 300, etc. may automatically make such a change using an "audio guidance device," or may notify the tour conductor of the tourist's level of interest and change the content of the information provided at the tour conductor's discretion.

[0132] Furthermore, the user may input their own personal information (such as name, address, and age), values, hobbies and interests, and desired conditions for spending holidays to the user terminal 100. In this case, the user terminal 100 may transmit the input personal information to the recommendation device 300, etc., and the recommendation device 300, etc. may provide information to the user based on the received personal information, etc. For example, the recommendation device 300, etc. may recommend information about hospitals, event venues, etc., near the user's home.

[0133] Furthermore, the recommendation device 300 etc. may provide the calculated index values ​​(stress value, pain value) to a medical institution. For example, when a user receives online medical care, the recommendation device 300 etc. may provide the calculated stress value or pain value acquired from the user terminal to a medical institution (doctor etc.) or event organization. Furthermore, the results obtained by online medical care (underlying diseases, pre-existing conditions) etc. may be used to determine who should be given priority for evacuation in the event of a disaster.

[0134] Furthermore, the recommendation device 300 etc. may issue "local currency" to users who participate in an event etc. in accordance with the recommendation information, or may request a local government etc. to issue "local currency." The local currency can contribute to revitalizing the local economy.

[0135] In the above-described second to fourth embodiments, the recommendation device 300 and the authentication device 200 have been described as separate information processing devices, but they may be the same. For example, the recommendation device 300 and the like may register facial feature information in association with the user ID 3121 of the user information 312. In this case, the control unit 340 may include the face detection unit 220, the feature point extraction unit 230, the registration unit 240, and the authentication unit 250 shown in FIG. 5.

[0136] In the above examples, the program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The program may be stored on a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable medium or tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0137] The present disclosure is not limited to the above-described embodiments, and may be modified as appropriate without departing from the spirit and scope of the present disclosure. In addition, the present disclosure may be implemented by appropriately combining the respective embodiments.

[0138] Some or all of the above embodiments can be described as, but are not limited to, the following supplementary notes. (Appendix A1) An acquisition means for acquiring status information of a predetermined user; a determination means for determining recommendation information based on the state information; an output means for outputting the determined recommendation information to a predetermined output destination; A recommendation device comprising: (Appendix A2) The determining means determines that the participation invitation to the first event is the recommended information. 10. The recommendation device according to claim A1. (Appendix A3) The determining means determines the recommendation information based on the status information, further including information about products or services that can be used when participating in the first event. Recommendation device according to Appendix A2. (Appendix A4) the acquiring means acquires first status information of the user before participating in the first event and second status information of the user after participating in the first event; The determining means derives a change in the user's state from the first state information to the second state information, and determines the recommendation information based on the derived change in state. 10. The recommendation device according to claim A2 or A3. (Appendix A5) the acquiring means acquires the status information from the user participating in the second event; the determining means determines the recommendation information based on the time or place at which the status information was acquired from the user and the status information; The output means outputs the determined recommendation information to a device on the organizer side of the second event as the output destination. The recommendation device according to any one of appendices A1 to A4. (Appendix A6) The determining means determines information relating to the presentation content of the second event as the recommendation information. Recommendation device according to Appendix A5. (Appendix A7) The output means outputs an instruction to apply the performance content of the second event. Recommendation device according to Appendix A6. (Appendix A8) the acquiring means acquires the status information and location information of each of a plurality of users participating in the second event; The determination means analyzes the emotion of each user from the state information, and determines, as the recommendation information, an emotion distribution of users for each area within a venue of the second event, based on the emotion and the location information. The recommendation device according to any one of appendices A5 to A7. (Appendix A9) the determining means further determines an application location of the effect content based on the emotion distribution; The output means specifies the application location and outputs an application instruction for the performance content of the event. Recommendation device according to Appendix A8. (Appendix A10) the acquiring means acquires the status information at a plurality of points in time from the user participating in the second event; The determining means derives a change in the state of the user from the state information at each time point, and determines the recommendation information based on the derived change in the state. The recommendation device according to any one of appendices A5 to A9. (Appendix A11) the acquiring means acquires a status report including the status information from a user terminal carried by the user; the recommendation device further includes a registration means for registering the status information and the user in association with each other; The determining means determines the recommendation information at a predetermined timing using one or more pieces of status information associated with the user. The recommendation device according to any one of appendices A1 to A10. (Appendix A12) The registration means registers personal authentication information for registration of the user in advance, the status report includes authentication information for authenticating the user; further comprising an identification means for identifying a user related to the status report by authentication using the personal authentication information for registration and authentication; The registration means registers the status information included in the status report in association with the specified user. 12. The recommendation device according to claim A11. (Appendix A13) The determining means Analyzing the status information to calculate an index value indicating the status of the user; The index value is used to determine the recommendation information. The recommendation device according to any one of appendices A1 to A12. (Appendix A14) The status information includes at least one of vital data measured from the user and a gait of the user detected by a detection device embedded in an insole worn by the user. The recommendation device according to any one of appendices A1 to A13. (Appendix A15) The acquiring means further acquires personal information of the user, The determining means determines the recommendation information based on the status information and the personal information. The recommendation device according to any one of appendices A1 to A14. (Appendix B1) a user terminal owned by a predetermined user; a recommendation device; The recommendation device acquiring means for acquiring status information of the user from the user terminal; a determination means for determining recommendation information based on the state information; an output means for outputting the determined recommendation information to a predetermined output destination; Equipped with Recommendation system. (Appendix B2) The determining means determines that the participation invitation to the first event is the recommended information. The recommendation system described in Appendix B1. (Appendix C1) The computer Obtaining state information for a given user; determining recommendation information based on the state information; The determined recommendation information is output to a predetermined output destination. How to recommend. (Appendix D1) An acquisition process for acquiring status information of a predetermined user; a determination process for determining recommendation information based on the state information; an output process of outputting the determined recommendation information to a predetermined output destination; A non-transitory computer-readable medium storing a recommendation program that causes a computer to execute the above.

[0139] Although the present invention has been described above with reference to the embodiments (and examples), the present invention is not limited to the above-described embodiments (and examples). Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. [Explanation of symbols]

[0140] 1 Recommendation device 11 Acquisition Department 12 Decision Section 13 Output section 1000 Recommendation Systems 2000 Recommender System 3000 Recommendation Systems N Network U0 User U1 user U2 users U3 users U4 users U5 Staff 100 user terminals 100-1 User terminal 100-2 User terminal 100-3 User terminal 100-4 User terminal 110 Camera 120 Storage section 121 Programs 122 Location information 123 Personal authentication information 130 memory 140 Communications Department 150 Input / output section 160 control section 161 Registration Department 162 Acquisition Department 163 Display control unit 200 Authentication Device 210 Face Information DB 211 User ID 212 Facial Feature Information 220 Face detection unit 230 Feature Point Extraction Unit 240 Registration Department 250 Authentication Department 300 Recommendation device 300a recommendation device 300b recommendation device 310 Storage section 311 Program 312 User Information 3121 User ID 3122 Personal Information 3123 Terminal Information 3124 Location information 3125 Status Information 3126 index value 3127 Recommendation History 320 memory 330 Communications Department 340 Control Unit 341 Acquisition Department 342 Registration Department 343 Authentication control section 344 Decision Section 345 Output Section 40 Event Venues 400 Emotion distribution 400a Emotion distribution 41 areas 42 areas 43 areas 44 areas 45 areas 46 areas 47 Locations where production changes are applied 401 Emotion distribution over time 410 Emotion distribution 411 Excitement 412 Joy 413 tension 420 Emotion distribution 421 Excitement 422 Joy 423 tension 424 Boredom 430 Emotion distribution 431 Great Enthusiasm 432 excitement 433 Joy 434 tension 435 Boredom 441 Production contents before change 442 Changed production content 443 Reason for change 500 Event Organizer Equipment 51 Recommendation screen 511 Recommendation information 512 Participation application button 52 Status change summary screen 521 Status Change 522 Status Change 53 Recommendation screen 531 Recommendation information 532 Participation application button 54 Recommendation screen 541 Production details before and after the change 542 Reason for change

Claims

1. An acquisition means for acquiring status information and location information of each of a plurality of users participating in an event that is held with a performance; a determination means for analyzing the emotions of each user from the state information, and determining, based on the emotions and the location information, an emotion distribution of users for each area in a venue of the event as recommendation information to be used for determining a presentation for each area of ​​the event in accordance with the emotion distribution; an output means for outputting the determined recommendation information to a device on the organizer side of the event; A recommendation device comprising:

2. The determining means determines information about the performance content of the event as the recommendation information. The recommendation device according to claim 1 .

3. The output means outputs an instruction to apply the performance content of the event. The recommendation device according to claim 2 .

4. The determining means further determines an application location of the performance content based on the emotion distribution, The output means specifies the application location and outputs an application instruction for the performance content of the event. The recommendation device according to claim 3 .

5. The determining means determines information relating to the production content of the event as the recommendation information in accordance with the change in the emotion distribution. The recommendation device according to claim 2 .

6. a user terminal owned by a predetermined user; a recommendation device; The recommendation device an acquisition means for acquiring status information and location information of a plurality of users participating in an event that is held with a performance from the user terminal of each of the users; a determination means for analyzing the emotions of each user from the state information, and determining, based on the emotions and the location information, an emotion distribution of users for each area in a venue of the event as recommendation information to be used for determining a presentation for each area of ​​the event in accordance with the emotion distribution; an output means for outputting the determined recommendation information to a device on the organizer side of the event; Equipped with Recommendation system.

7. The computer Acquire status information and location information of each of a plurality of users participating in an event that is held with a performance; analyzing the emotions of each user from the state information, and determining an emotion distribution of users for each area within a venue of the event based on the emotions and the location information as recommendation information to be used for determining a presentation for each area of ​​the event in accordance with the emotion distribution; The determined recommendation information is output to a device on the organizer side of the event. How to recommend.

8. An acquisition process for acquiring status information and location information of each of a plurality of users participating in an event that is held with a performance; a determination process of analyzing the emotions of each user from the state information, and determining, based on the emotions and the location information, an emotion distribution of users for each area within a venue of the event as recommendation information to be used for determining a performance for each area of ​​the event in accordance with the emotion distribution; an output process of outputting the determined recommendation information to an apparatus on the organizer side of the event as an output destination; A recommendation program that causes a computer to run the following.

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