WO2023032204A1 - Recommendation device, system, method, and computer-readable medium - Google Patents

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

Recommendation device, system and method, and computer readable medium

The present invention relates to recommendation devices, systems and methods, and computer-readable media.

Patent Document 1 discloses a technology related to a life support device that grasps a user's behavior, stress/fatigue, and other situations, and displays corresponding life navigation services and advertisements.

JP-A-2001-344352

Here, the user's state may change due to the user's participation in a predetermined event. Therefore, it can be said that the services and information suitable for the user differ depending on the user's state and how it changes.

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 condition in view of the above-described problems.

A recommendation device according to a first aspect of the present disclosure includes:
Acquisition means for acquiring status information of a predetermined user;
determining means for determining recommended information based on the state information;
output means for outputting the determined recommendation information to a predetermined output destination;
Prepare.

A recommendation system according to a second aspect of the present disclosure includes:
a user terminal possessed by a predetermined user;
a recommendation device;
The recommendation device is
Acquisition means for acquiring the state information of the user from the user terminal;
determining means for determining recommended information based on the state information;
output means for outputting the determined recommendation information to a predetermined output destination;
Prepare.

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.

A recommendation program according to the fourth aspect of the present disclosure includes:
an acquisition process for acquiring status information of a given user;
a determination process for determining recommended information based on the state information;
an output process of outputting the determined recommendation information to a predetermined output destination;
run on the computer.

With the present disclosure, it is possible to provide a recommendation device, system, method, and program for recommending appropriate information according to the user's condition.

1 is a block diagram showing the configuration of a recommendation device according to the first embodiment; FIG. 4 is a flow chart showing the flow of a recommendation method according to the first embodiment; FIG. 11 is a block diagram showing the overall configuration of a recommendation system according to a second embodiment; FIG. FIG. 9 is a block diagram showing the configuration of a user terminal according to the second embodiment; FIG. FIG. 11 is a block diagram showing the configuration of an authentication device according to the second embodiment; FIG. FIG. 11 is a block diagram showing the configuration of a recommendation device according to a second embodiment; FIG. 9 is a flowchart showing the flow of user registration processing according to the second embodiment; 9 is a flow chart showing the flow of face information registration processing by the authentication device according to the second embodiment; 10 is a flow chart showing the flow of status report processing according to the second embodiment; 9 is a flow chart showing the flow of face authentication processing by the authentication device according to the second embodiment; FIG. 11 is a flow chart showing the flow of a first recommendation process according to the second embodiment; FIG. FIG. 11 is a diagram showing a display example of recommendation information according to the second embodiment; FIG. 11 is a block diagram showing the overall configuration of a recommendation system according to a third embodiment; FIG. FIG. 16 is a flow chart showing the flow of a second recommendation process according to the third embodiment; FIG. FIG. 12 is a diagram showing display examples of index values before and after participation according to the third embodiment; FIG. 13 is a diagram showing a display example of recommendation information according to the third embodiment; FIG. 12 is a block diagram showing the overall configuration of a recommendation system according to a fourth embodiment; FIG. FIG. 16 is a flow chart showing the flow of a third recommendation process according to the fourth embodiment; FIG. FIG. 14 is a flow chart showing the flow of a fourth recommendation process according to the fourth embodiment; FIG. FIG. 14 is a diagram showing a display example of emotion distribution according to the fourth embodiment; FIG. 14 is a diagram showing an example of changes in emotion distribution along a time series according to the fourth embodiment; FIG. 21 is a diagram showing display examples of effect contents and change reasons before and after change according to the fourth embodiment; FIG. 14 is a diagram showing a display example of emotion distribution according to the fourth embodiment;

Below, embodiments of the present disclosure will be described in detail with reference to the drawings. In each drawing, the same reference numerals are given to the same or corresponding elements, and redundant description will be omitted as necessary for clarity of description.

<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 recommended information suitable for the user according to state 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 will simply be referred to as a network) or predetermined wireless communication. It does not matter whether the network is wired or wireless, and the type of communication protocol does not matter. The terminal transmits state information of the user to the recommendation device 1 . Also, the terminal may perform processing according to the output from the recommendation device 1 . The terminal may be a user terminal or the like that the user possesses or wears.

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, 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, and text information such as the user's current mood and impression of participating in an event. However, the status information is not limited to these.

The determining unit 12 determines recommended information based on the state information. Here, the recommendation information is information for recommending (providing) to the user related to the state information. For example, the recommended information is event information, guidance information on medical institutions or facilities, introduction information on products and services, provision information on health, and the like. However, the recommended information is not limited to these. The determination unit 12 may determine recommendation information using a recommendation model that receives state information and the like and outputs recommendation information based on a predetermined logic. Note that a known technique such as an AI (Artificial Intelligence) model can be applied to the recommendation model. Also, the recommendation model can be machine-learned using teacher data in which state information and the like are input data and the adoption result of the recommendation information is correct data.

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 that can be viewed by related parties (family members, relatives, etc.) of the user, and relationships such as events and facilities related to the recommended information. It is an information processing device or the like that can be browsed by a person. However, the output destination is not limited to these.

FIG. 2 is a flow chart 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).

As described above, the recommendation device 1 according to the present embodiment determines recommendation information in consideration of the status information acquired from the user. Therefore, the recommendation device 1 can recommend appropriate information according to the state of the user.

The recommendation device 1 includes a processor, a memory, and a storage device (not shown). Further, the storage device stores a computer program in which the processing of the recommendation method according to the present embodiment is implemented. Then, the processor loads the computer program from the storage device into the memory and executes the computer program. Thereby, the processor implements the functions of the acquisition unit 11 , the determination unit 12 and the output unit 13 .

Alternatively, each component of the recommendation device 1 may be realized by dedicated hardware. Also, part or all of each component of each device may be implemented by general-purpose or dedicated circuitry, processors, etc., or combinations thereof. These may be composed of a single chip, or may be composed of multiple chips connected via a bus. A part or all of each component of each device may be implemented by a combination of the above-described circuits and the like and programs. As a processor, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an FPGA (Field-Programmable Gate Array), a quantum processor (quantum computer control chip), or the like can be used.

Further, when some or all of the components of the recommendation device 1 are implemented by a plurality of information processing devices, circuits, etc., the plurality of information processing devices, circuits, etc. may be centrally arranged or distributed. may be placed. For example, the information processing device, circuits, and the like may be implemented as a form in which each is connected via a communication network, such as a client-server system, a cloud computing system, or the like. Also, the functions of the recommendation device 1 may be provided in a SaaS (Software as a Service) format.

<Embodiment 2>
The second embodiment is a specific example of the first embodiment described above. FIG. 3 is a block diagram showing the overall configuration of a recommendation system 1000 according to the second embodiment. The recommendation system 1000 is an information system for determining recommendation information suitable for the user U0 according to the state information and personal information of the user U0 and making recommendations to the user U0 and related parties.

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 via a network N, respectively. Here, the network N is a wired or wireless communication line such as the Internet.

In the following explanation, "identity authentication information" is information used for authentication of identity confirmation (personal authentication, identity identification processing, etc.), and is information for uniquely identifying (identifying) the person. In addition, in the present embodiment, personal authentication will be described as face authentication, which is an example of biometric authentication, and personal authentication information (personal identification information) will be described as facial feature information, which is an example of biometric information. However, biometric authentication and biometric information can be applied to other techniques that use a photographed image of a person. For example, biometric information may be data (feature amounts) calculated from physical features unique to an individual, such as fingerprints, voiceprints, veins, retinas, irises, and palm patterns. Also, instead of biometric authentication, other personal authentication may be applied, and the biometric information may also be other personal authentication information. For example, personal authentication information includes a user ID, a combination of an ID and a password, the contents of an identification card such as my number or driver's license (identification number and password), an electronic certificate, code information, and the like. , but not limited to. The code information may be a two-dimensional code such as a QR code (registered trademark).

The user terminal 100 is an information terminal that the user U0 possesses, carries, operates, or wears, and that 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 smart phone, a tablet terminal, a wearable terminal, or the like. In addition, the user terminal 100 performs short-range wireless communication with a wearable device worn by the user U0 or an insole sensor embedded in the shoe of the user U0, and obtains detection results or measurement results from the wearable device or the insole sensor. good too. In this case, the user terminal 100 regards the acquired detection result or measurement result as at least part of the participant's state information.

FIG. 4 is a block diagram showing the configuration of the user terminal 100 according to the second embodiment. User terminal 100 includes camera 110 , storage unit 120 , memory 130 , communication unit 140 , input/output unit 150 and control unit 160 . The camera 110 is an imaging device that performs imaging under the control of the control unit 160 . The storage unit 120 is an example of a storage device including non-volatile memory such as flash memory and 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 in which processing including user registration processing, participant status information acquisition processing, status reporting processing, recommendation information display processing, and the like, which will be described later, is implemented. 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 specifying the user carrying the user terminal 100 . The personal authentication information 123 may be biometric information such as a facial image, facial feature information, or other personal identification information as described above.

The memory 130 is a volatile storage device such as RAM (Random Access Memory), and is a storage area for temporarily holding information when the control unit 160 operates. The communication unit 140 is a communication interface with the network N. FIG. 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 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. Thereby, the control unit 160 realizes the functions of the registration unit 161 , the acquisition unit 162 and the display control unit 163 .

The registration unit 161 performs user information registration processing. Specifically, the registration unit 161 receives the face image and personal information of the user U0 input by the user U0. The registration unit 161 transmits a registration request for user information including the received face image and personal information to the recommendation device 300 via the network N. FIG. Note that the registration unit 161 may include other personal authentication information in the registration request for registration instead of the face image. The registration unit 161 may receive the user ID issued at the time of registration of the user information from the recommendation device 300 via the network N and register it in the storage unit 120 as the personal authentication information 123 .

In addition, the registration unit 161 performs status report processing. Specifically, the registration unit 161 sends a state report including the state information, the current position, and the face image (personal authentication information) acquired by the acquisition unit 162 as described later via the network N at any timing. and transmits it to the recommendation device 300 . Note that the registration unit 161 may include other personal authentication information in the status report for authentication instead of the face image. In other words, registration unit 161 does not necessarily need to transmit a face image each time a status report is made. In addition, the registration unit 161 may perform the status reporting process periodically. Incidentally, the status reporting process does not necessarily have to be performed periodically. For example, the registration unit 161 may perform the state reporting process for the state information acquired by the acquisition unit 162 when a change in state is detected from the state information acquired so far.

In addition, the registration unit 161 receives information (adoption result) indicating whether or not the recommendation information displayed on the display control unit 163 (to be described later) is input by the participant, and sends the adoption result to the recommendation device via the network N. 300.

The acquisition unit 162 performs user status information acquisition processing. The state information includes the user's health condition, degree of satisfaction (events attended, recommended places to visit, etc.), preference information, behavior information, and the like. Specifically, the acquisition unit 162 acquires measured values (vital data) such as the user's body temperature, pulse rate, heart rate, etc., as the state of health. For example, the acquisition unit 162 acquires a measured value from a health condition measuring instrument. The health condition measuring instrument may be built in the user terminal 100 when the user terminal 100 is a wearable terminal. Alternatively, the acquisition unit 162 may acquire the measured value from a wearable terminal or the like worn by the user through short-range wireless communication. Alternatively, the health condition may be gait information of the user detected by a detection device (insole sensor) embedded in the insole (insole of the shoe) worn by the user. The gait information includes information indicating stride length, walking speed, ground contact angle, outside turning distance (toe direction, foot lift height), take-off angle, and the like. For example, the acquisition unit 162 may acquire the detected value of the gait information as the state of health from the insole sensor through short-range wireless communication. The acquisition unit 162 may also acquire, as the health condition, an input value from the user on the health condition report screen. The input value may be, for example, health information such as body temperature, or an answer (selected value such as physical condition, degree of fatigue, etc., or text information) displayed on the report screen. In addition, the acquisition unit 162 may perform the state information acquisition process periodically. Periodic means, for example, every hour or once a day, but the interval is not limited to these. Alternatively, the acquisition unit 162 may perform the state information acquisition process not only periodically, but at any timing such as a request from the user.

In addition, the acquisition unit 162 may acquire, as state information, the degree of satisfaction with respect to the event in which the user has participated or the recommended visiting place. For example, the acquisition unit 162 may acquire an input value (numerical value, level value, text information, etc.) from the user on the satisfaction level input screen as the satisfaction level. Alternatively, the acquisition unit 162 acquires a photographed image of the user photographed by the camera 110 while participating in the event, and acquires the degree of smile or mood determined based on the result of predetermined analysis of the photographed image as the degree of satisfaction. may

Also, the acquisition unit 162 may acquire input values (hobbies, cooking preferences, etc.) from the user on the input screen as preference information. In addition, the acquisition unit 162 may acquire input values (visited places, purchase history, etc.) from the user on the input screen as behavior information.

Also, the acquisition unit 162 acquires GPS information indicating the current position of the user terminal 100 via the communication unit 140 as position information, and stores it in the storage unit 120 as position information 122 . Further, the acquisition unit 162 may acquire an image of the user captured by the camera 110 while participating in the event, and store it in the storage unit 120 as the personal identification information 123 .

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 .

Returning to FIG. 3, the description continues.
The authentication device 200 is an information processing device that manages user's facial feature information. In addition, in response to a face authentication request received from the outside, the authentication device 200 compares the face image or face feature information included in the request with the face feature information of each user, and requests the result of matching (authentication result). Reply to original.

FIG. 5 is a block diagram showing the configuration of the authentication device 200 according to the second embodiment. The authentication device 200 includes a face information DB (DataBase) 210 , a face detection section 220 , a feature point extraction section 230 , a registration section 240 and an authentication section 250 . The face information DB 210 associates and stores a user ID 211 and face feature information 212 of the user ID. The facial feature information 212 is a set of feature points extracted from the facial image. Note that the authentication device 200 may delete the facial feature information 212 in the facial feature DB 210 in response to a request from a user or the like corresponding to the facial feature information 212 . Alternatively, authentication device 200 may delete facial feature information 212 after a certain period of time has passed since registration.

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

The registration unit 240 newly issues a user ID 211 when registering facial feature information. The registration unit 240 associates the issued user ID 211 with the facial feature information 212 extracted from the registered image and registers them in the facial information DB 210 . Authentication unit 250 performs face authentication using facial feature information 212 . Specifically, the authentication unit 250 collates the facial feature information extracted from the facial image with the facial feature information 212 in the facial information DB 210 . If the verification is successful, the authentication unit 250 identifies the user ID 211 associated with the verified facial feature information 212 . The authenticating unit 250 replies to the requester as a face authentication result indicating whether or not the facial feature information matches. Whether the facial feature information matches or not corresponds to the success or failure of the authentication. Note that matching of facial feature information (matching) means a case where the degree of matching is equal to or greater than a threshold. Also, the face authentication result shall include the specified user ID when the face authentication is successful.

Returning to FIG. 3, the description continues.
The recommendation device 300 is an example of the recommendation device 1 described above. The recommendation device 300 is an information processing device that performs user registration processing, status report processing, first recommendation processing, and the like (recommendation method according to the second embodiment). The recommendation device 300 may be made redundant by a plurality of servers, and each functional block may be implemented by a plurality of computers.

FIG. 6 is a block diagram showing the configuration of the 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, flash memory, SSD, or the like. The storage unit 310 stores programs 311 and user information 312 . A program 311 is a computer program in which the processing of the recommendation method according to the second embodiment is implemented.

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, position information 3124, state information 3125, index values 3126, and recommendation history 3127 are associated with each other. User ID 3121 is user identification information. The user ID 3121 is information identically or uniquely corresponding to the user ID 211 managed in association with the facial feature information 212 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 personal authentication information for registration of the user via the user ID 3121 .

The personal information 3122 may include the user's name, gender, date of birth, address, nationality, contact information, payment information, and the like. The personal information 3122 may also include the user's medical information (medical history), health information (allergy information), hobbies and preferences, and the like. Personal information 3122 may also include information on the user's family.

The terminal information 3123 is information that serves as a notification destination for the user terminal 100 owned by the user. The terminal information 3123 is, for example, a mobile phone number, an e-mail address, an application user ID, a social network service account, and the like. The location information 3124 is information indicating the current location of the user terminal 100 possessed by the user. Also, the location information 3124 may be a history of location information. Status information 3125 is the status information included in the status report described above. Also, the state information 3125 may be a history of state information.

The index value 3126 is an index value indicating the state of the user calculated from the state information 3125 and the like by analysis described later. The index value 3126 can also be said to be information that quantifies the state of the user. For example, the index value 3126 expresses the user's degree of stress, degree of pain, severity of symptoms, etc. by numerical values, frequencies, ratios, the presence or absence of flags, values indicating levels, and the like. Also, the index value 3126 may be information indicating the user's emotion, such as pleasantness or discomfort, the presence or absence and degree of wakefulness, the degree of drowsiness, and the like.

The recommendation history 3127 is a history of recommendation information recommended for the user. The recommendation history 3127 may include the date and time of recommendation, contents (events, etc.), user participation (adoption), and the like.

The memory 320 is a volatile storage device such as RAM (Random Access Memory), and is a storage area for temporarily holding information when the control unit 340 operates. A communication unit 330 is a communication interface with the network N. FIG.

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

The acquisition unit 341 is an example of the acquisition unit 11 described above. In the following description, the acquisition unit 341 "acquires" information via the network N may be expressed as the acquisition unit 341 "receives" information. The acquisition unit 341 receives a user information registration request from the user terminal 100 . The registration request includes personal authentication information (face image, etc.) for user registration and personal information. Also, the acquisition unit 341 receives a status report from the user terminal 100 . The status report includes user status information, current location, and personal authentication information for authentication (face image, etc.). Furthermore, the acquisition unit 341 may receive the adoption/non-adoption result for the recommendation information from the user terminal 100 .

The registration unit 342 generates user information 312 and registers it in the storage unit 310 based on the received registration request. Specifically, registration unit 342 transmits a face information registration request including the face image included in the registration request to authentication device 200 . Then, the registration unit 342 acquires the user ID issued by the authentication device 200 in accordance with the registration of the face information. Alternatively, when the authentication device 200 is not used for personal authentication processing, the registration unit 342 may issue a new user ID. The registration unit 342 generates user information 312 by associating the issued user ID 3121 with the personal information 3122 included in the registration request and the terminal information 3123 of the user terminal 100 that requested the registration. As described above, since the user ID is associated with the facial feature information, it can be said that the registration unit 342 preliminarily registers the personal authentication information for registration of the user and the personal information as user information in association with each other.

Also, the registration unit 342 updates the user information 312 by associating the location information 3124 and the state information 3125 included in the received state report with the user ID 3121 of the user authenticated by the authentication control unit 343 . Further, the registration unit 342 updates the user information 312 by associating the index value 3126 of the user calculated by the determination unit 344 (to be described later) with the user ID 3121 of the corresponding user. In addition, the registration unit 342 updates the user information 312 by adding recommended information determined by the determining unit 344 (to be described later) and adoption/non-adoption results for the recommended information to the recommendation history 3127 . Note that the registration unit 342 adds the location information 3124, the status information 3125, the index value 3126, and the recommendation history 3127 to the user information 312 that has been initially registered in the storage unit 310 by updating the user information 312. It may be expressed as registering as Therefore, it can be said that the registration unit 342 registers the location information 3124 and the state information 3125 included in the received state report in association with the user ID 3121 of the user identified by the authentication control unit 343 .

The authentication control unit 343 controls face authentication for the face image included in the received status report. Specifically, authentication control unit 343 transmits a face authentication request including a face image to authentication device 200 and receives a face authentication result from authentication device 200 . Then, the authentication control unit 343 determines success or failure of the authentication from the face authentication result received from the authentication device 200, and specifies the user ID included in the face authentication result when the authentication is successful. Note that the authentication control unit 343 may detect the user's face area from the face image and include the 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.

However, as described above, personal authentication is not limited to face authentication, and the authentication control unit 343 may control authentication using personal authentication information for registration and authentication. In other words, when the status report contains personal authentication information other than a face image, the authentication control unit 343 appropriately selects the personal authentication information for registration registered in the authentication device or inside according to the type of the personal authentication information. Authentication is performed by controlling matching with Then, when the authentication is successful, the authentication control unit 343 identifies the corresponding user ID. Therefore, the authentication control unit 343 can be said to be a specifying means for specifying the user for the status report by authentication using the personal authentication information for registration and authentication.

The determination unit 344 is an example of the determination unit 12 described above. The determining unit 344 determines recommended information based on the state 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 state information associated with the target user. Here, the predetermined timing includes when a status report is received, that is, when status information is additionally registered, when there is a recommendation request from the user terminal 100 or others, regular timing, arbitrary timing, or the like. is included. Also, the determining unit 344 may determine recommended information based on the target user's state information and personal information. That is, the determination unit 344 uses at least one of the target user's health condition such as vital data or gait information, satisfaction level of the event they participated in, and attribute information such as family composition and hobbies and tastes to obtain recommended information. may be determined. For example, the determination unit 344 determines the invitation to participate in the first event as the recommendation information. Furthermore, the determining unit 344 may determine the recommended information further including guide information of products or services that can be used when participating in the first event, based on the state information.

Also, the determining unit 344 may analyze the state information, calculate an index value indicating the state of the target user, and determine the recommended information using the index value. Specifically, the determining unit 344 performs data analysis on 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 state such as stress and pain. Also, the determination unit 344 may calculate a plurality of index values corresponding to a plurality of types of indices. Also, the recommendation device 300 does not necessarily need to calculate the index value when determining the recommendation information.

For example, the determining unit 344 calculates, as an index value, a stress value that quantifies the stress felt by the user based on the vital data. For example, the determination unit 344 may calculate different stress values depending on whether the pulse is faster or slower than a predetermined value. The determining unit 344 also calculates a pain value, which is a numerical value representing pain felt by the user based on the gait information, as an index value. For example, the determining unit 344 may comprehensively determine the stride length, walking speed, contact angle, turning distance, take-off angle, and the like to quantify the degree of back pain or knee pain and calculate the pain value. The determination unit 344 may also calculate the user's emotion (the degree of enjoyment or boredom) or the like as an index value based on vital data or the like. Furthermore, the determining unit 344 may perform data analysis with attribute information of the target user taken into account.

Alternatively, the determination unit 344 may calculate a feature amount from the tendency of changes in time series for vital data measured at a plurality of points in time for a specific user, and analyze the feature amount using a predetermined algorithm. Then, the determining unit 344 may calculate each index value by classifying a plurality of types of indexes from the analysis result. For example, the determination unit 344 performs heart rate variability analysis from time-series heart rate data, and classifies each of the two types of emotional indices of wakefulness/drowsiness and comfort/discomfort. In other words, the user's emotions may be divided into four quadrants by biaxially dividing them into wakefulness/drowsiness and comfort/discomfort.

Then, the determination unit 344 preferably inputs the calculated index value to a recommendation model or the like to determine recommendation information. Alternatively, the determination unit 344 may transmit a recommendation request including the calculated index value to an external server having a recommendation model, and receive recommendation information from the server. Alternatively, the determining unit 344 may receive auxiliary information for determining recommended information instead of the recommended information itself from the server, and input the auxiliary information into a recommendation model or the like to determine recommended information. good. Furthermore, the determination unit 344 may transmit a recommendation request to multiple servers and collect recommendation information or auxiliary information from each server. In that case, the determination unit 344 may select part of the collected recommendation information as the recommendation information. Alternatively, the determining unit 344 may collect auxiliary information and use it as recommended information. Furthermore, the determination unit 344 may determine, as recommendation information, attached information, guide information, or advertisement information of a service to be recommended to the target user. The ancillary information may be introductory information about products or services that can be used when participating in a recommended event or when using a service.

The output unit 345 is an example of the output unit 13 described above. The output unit 345 outputs the determined recommendation information to the user terminal 100 of the target user. Also, the output unit 345 may output the determined recommendation information to the terminal of the relevant person of the target user. The output by the output unit 345 to the user terminal 100 or the like may also be expressed as the output unit 345 transmitting to the user terminal 100 or the like.

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 the user U0 performs user registration using the user terminal 100 in order to receive recommendations for events suitable for him or his family. In that case, the user terminal 100 receives an input of the user U0's face image and personal information from the user U0. For example, the user terminal 100 captures the vicinity of the face of the user U0 with the camera 110 and acquires the face image. Note that the user terminal 100 may accept other personal authentication information of the user U0 instead of the face image. The user terminal 100 also displays a personal information input screen and accepts input of personal information from the user U0. At this time, the user terminal 100 receives the user's name, gender, date of birth, address, nationality, contact information, payment information, medical information (previous history), health information (allergy information), hobbies and preferences, family information, etc. may be accepted. The family information may include family composition, family personal information, family tastes and preferences, family personal authentication information, and the like. For example, the user terminal 100 may use an input screen for receiving such information in a selection format. Furthermore, the user terminal 100 may accept a rental request for a wearable terminal for easily acquiring state information from the user U0. The wearable terminal shall be delivered to the user when rental is requested. After that, the user terminal 100 transmits a user information registration request including the face image and personal information of the user U0 to the recommendation device 300 via the network N. FIG.

FIG. 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 user information registration request from the user terminal 100 via the network N. FIG. That is, the acquisition unit 341 receives a registration request including the face image and personal information of the user U0 (S301). Next, the registration unit 342 transmits a face information registration request including the face image included in the registration request to the authentication device 200 (S302).

FIG. 8 is a flow chart showing the flow of face information registration processing by the authentication device according to the second embodiment. Here, the information registration terminal (not shown) photographs the user's body including the face, and transmits a face information registration request including the photographed image (registered 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 smart phone, or a tablet terminal. For example, the information registration terminal may be the user terminal 100 or the like. Here, it is assumed that the information registration terminal is the recommendation device 300 that has received a registration request from the user terminal 100 or the like.

First, the authentication device 200 receives a face information registration request (S201). For example, the authentication device 200 receives a face information registration request via the network N from the recommendation device 300 . Next, the face detection unit 220 detects a face area from the 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 the 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 facial information DB 210 (S205). After that, the registration unit 240 returns the issued user ID 211 to the request source (the information registration terminal, for example, the recommendation device 300) (S206).

Return to Fig. 7 and continue the explanation. The registration unit 342 of the recommendation device 300 acquires the user ID issued according to the registration of the face information from the authentication device 200 (S303). If the registration request does not include the face image of the user U0 or the personal authentication information, the registration unit 342 newly issues the user ID as the personal authentication information. The registration unit 342 identifies the personal information included in the registration request, and identifies the terminal information of the user terminal 100 that is the source of the registration request. Note that the terminal information may be included in the registration request. After that, the registration unit 342 generates the user information 312 by associating the acquired or issued user ID 3121, the specified personal information 3122, and the specified terminal information 3123 with each other. 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. FIG. At this time, the user terminal 100 may store the received user ID in the storage unit 120 as the personal authentication information 123 .

Next, the status reporting process will be explained. The user terminal 100 acquires state information from the user U0 at arbitrary timing by 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 the read personal authentication information (face image, etc.), the position information (current position), and the status report including the acquired status information to the recommendation device 300 via the network N. Note that the user terminal 100 determines whether or not the change in state of the acquired state information is within a certain range compared to the state information acquired so far, and if the change exceeds the certain range, the user terminal 100 transmits a status report. good too. As a result, when the state change is within a certain range, the state information transmission processing is not performed, so the amount of communication and the number of times of communication can be suppressed. In addition, the recommendation device 300 can assume that the health condition of a particular user is constant while no condition report is received from the user.

FIG. 9 is a flowchart showing the flow of status report processing according to the second embodiment. 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.

Next, the authentication control unit 343 identifies the user through final authentication with respect to the personal authentication information included in the received status report (S312). Specifically, the authentication control unit 343 performs authentication by controlling matching between the personal authentication information for authentication included in the status report and the personal authentication information registered in advance. The authentication control unit 343 identifies the user by the user ID associated with the successfully authenticated personal authentication information for registration.

Below, an example in which personal authentication is face authentication will be explained. In this case, authentication control unit 343 transmits a face authentication request including the face image included in the received status report to authentication device 200 via network N. FIG. In response to this, the authentication device 200 performs face authentication processing.

FIG. 10 is a flow chart 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). Note that the authentication device 200 may 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, as in steps S202 and S203 described above. Then, the authentication unit 250 of the authentication device 200 collates the facial feature information extracted from the face image included in the face authentication request with the facial feature information 212 of the face information DB 210 (S212), and calculates the matching degree. Then, the authentication unit 250 determines whether or not the degree of matching is equal to or greater than the threshold (S213). If the facial feature information matches, that is, if the degree of matching 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 result of the face authentication including the result of the successful face authentication and the identified user ID 211 to the recommendation device 300 via the network N (S215). If the degree of matching is less than the threshold in step S213, the authenticating unit 250 returns the face authentication result including the failure of the face authentication to the recommendation device 300 via the network N (S216).

Return to Fig. 10 and continue the explanation. 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 the face authentication is successful based on the received face authentication result. When determining that the face authentication has succeeded, the authentication control unit 343 identifies the user ID included in the face authentication result and identifies the user ID as the user. On the other hand, when face authentication fails, the recommendation device 300 may reply to the user terminal 100 to that effect.

Here, we will continue the explanation assuming that face recognition has succeeded. At this time, the registration unit 342 registers the current position and state information included in the state report in the user information 312 of the identified user (S313). Specifically, the registration unit 342 acquires the current position and state information included in the state report, and updates the participant information 312 by associating the position information 3124 and the state information 3125 with the user ID 3121 whose face authentication has succeeded. .

FIG. 11 is a flow chart 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, a case where the recommendation device 300 receives a recommendation request from the user terminal 100 periodically after execution of the status report process. For example, the user terminal 100 accepts a recommendation request for an experience-based 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.

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 arbitrary user information from among the plurality of pieces of user information 312 . Alternatively, the determination unit 344 selects the user ID whose status report is registered as the target user. Alternatively, the determination unit 344 selects the user ID corresponding to the personal authentication information included in the recommendation request as the target user.

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

Then, the determining unit 344 determines recommended information using the calculated index value, as described above (S334). A specific example of steps S333 and S334 will be described later.

After that, the output unit 345 outputs the determined recommended 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 recommended information to the specified terminal information. In response, the user terminal 100 displays the received recommendation information on the input/output unit 150 as a recommendation screen.

FIG. 12 is a diagram showing a display example 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 guide information to a participatory event as recommendation information. The participatory event recommendation screen 51 includes recommendation information 511 and a participation application button 512 . The recommendation information 511 is an example showing, for example, the name of the participatory event to be recommended, the date and time of the event, an explanation, the target age group (participation conditions), and the location of the event. When the participation application button 512 is pressed, a screen for inputting or selecting a participant name is displayed.

When the user terminal 100 accepts input or selection of participant names, the user terminal 100 sends 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. Send. The recommendation device 300 performs application processing for the event based on the information included in the received participation application request. Note that if the event for which the application is made is charged, the recommendation device 300 uses the payment information included in the personal information 3122 associated with the user ID 3121 to settle the usage fee. After that, the user U1 can go to the participatory event site with his family and participate in the event.

Here, we will explain how to determine the recommended information for the user and specific examples of the recommended information. For example, the recommendation device 300 may recommend (provide information to) the user recommended information determined based on the stress value or pain value calculated as the index value in step S333. For example, when the stress value is higher than a predetermined value, the recommendation device 300 may determine recommendation information related to places, events, and the like where the user can relax. In addition, when the pain value related to low back pain calculated from the gait information or the like is higher than a predetermined value, that is, the user suffering from low back pain, the recommendation device 300 selects a hospital, facility, or the like where guidance on how to walk can be provided. Guidance information may be determined as recommended information. Also, the recommendation device 300 may determine the user's health condition based on the stress value and the pain value, and recommend recommendation information determined based on the determination result to the user. For example, when the stress value and the low back pain are lower than predetermined values, the recommendation device 300 determines that the health condition of the user is "excellent". On the other hand, if the stress value is higher than the predetermined value and the user has low back pain, the recommendation device 300 determines that the health condition of the user is "poor". Then, the recommendation device 300 may provide health-related information to the user whose health condition is determined to be "poor".

In addition, the recommendation device 300 calculates the degree of symptoms of lifestyle-related diseases as an index value from medical information (pastoral history) and the like included in the personal information and state information such as vital data, and recommends information for alleviating the symptoms. Decisions should be made as information. In addition, when the user is an elderly person, the recommendation device 300 calculates an index value of the user's health status from state information, medical information, etc. It is preferable to determine advice on health that differs from person to person as recommended information. These can contribute to the health promotion of the user.

In addition, the recommendation device 300 uses the state information, the hobby and taste, the family information, and the like included in the personal information to provide guidance information regarding products to be sold, services to be provided, and participatory events as recommendation information. you should decide. For example, the recommendation device 300 may determine outdoor experiences as participatory events as recommendation information. In this case, the operator of the recommendation device 300 may tie up with an outdoor manufacturer and rent equipment (such as a tent) necessary for experiencing the event. In other words, when recommending a participatory event, the recommendation device 300 may also include in the recommendation information introduction information on rental equipment such as equipment that can be used at the event. As a result, the user can easily apply for equipment rental at the time of applying for participation in the event, and can easily determine whether or not to purchase the rented equipment after experiencing the event. Therefore, it can contribute to the sales improvement of outdoor manufacturers.

Also, the operator of the recommendation device 300 may cooperate with a local government or the like in a specific area to provide information on the area. For example, it is assumed that the cooperating municipalities have tourism resources such as the sea, mountains, and rivers. At this time, the recommendation device 300 selects users who live near a specific area as target users based on the address included in the personal information 3122 in the user information 312 . Then, the recommendation device 300 may determine, as recommendation information, an exercise experience, a meal, and the like in the region based on the target user's state information, personal information (hobbies, preferences, family information), and the like. This will contribute to regional revitalization.

In addition, the recommendation device 300 may determine administrative services in a specific area as recommendation information for residents, commuters, school commuters, and the like in the area. At this time, the recommendation device 300 selects the target user based on the information such as the address, workplace, school, etc. included in the personal information 3122 in the user information 312 . Then, the recommendation device 300 may determine, as recommendation information, guidance for a health checkup to be carried out in the area based on the target user's condition information and an index value relating to the health condition. Note that the method of determining recommended information and specific examples of recommended information are not limited to those described above.

As described above, the recommendation device 300 according to the present embodiment performs data analysis using regularly registered user status information and pre-registered personal information, etc., to obtain various indicators indicating user status. Obtain an index value that quantifies The recommendation device 300 determines recommended information using the index value and provides information to the user. Therefore, it is possible to recommend appropriate information according to the user's condition.

<Embodiment 3>
Embodiment 3 is a modification of Embodiment 2 described above. The recommendation device 300a according to the third embodiment acquires the user's impression of the user's experience based on the recommendation information, changes in the user's health condition according 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 a change in emotion obtained by the user actually participating in a recommended event or the like, and use the acquired information to determine further recommended information.

FIG. 13 is a block diagram showing the overall configuration of the recommendation system 2000 according to the third embodiment. In the following description, the same reference numerals are given to the same configurations as those of the second embodiment, and illustration and detailed description thereof are omitted. A recommendation system 2000 is obtained by replacing the recommendation device 300 described above with a recommendation device 300a. Also, in the recommendation system 2000, it indicates that the user U0 possessing the user terminal 100 has participated in the first event held at the event venue 40. FIG. Here, the first event may be an event that accompanies a participant's experience, or may be an event such as viewing. For example, the first event may be an event that is recommended to the user U0 according to the second embodiment described above and that the user U0 participates in based on the recommendation information. Alternatively, the first event may be one that the user U0 voluntarily participates in without being recommended.

The recommendation device 300a is an improvement of the above-described recommendation device 300, and provides recommendation information to the user U0 in consideration of the state information of the user U0 before and after participating in the event. Specifically, the acquisition unit of the recommendation device 300a acquires first state information of the user U0 before participating in the first event, second state information of the user after participating in the first event, to get Also, the determination unit of the recommendation device 300a derives a change in the state of the user U0 from the first state information to the second state information, and determines recommendation information based on the derived state change. Here, the recommended information may be guide information to the second event, or may be the above-described various recommended information other than the event. The recommendation information may include at least a change in the state associated with the user U0's participation in the event.

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

First, the recommendation device 300a performs registration processing of the state report of the user U0 after participating in the first event (S320). Specifically, after the user U0 participates in the first event at the event venue 40, the user terminal 100 acquires status information from the user U0 by various means as described above. Then, as described above, the user terminal 100 recommends, via the network N, a status report including the identity authentication information of the user U0, the location information of the event venue 40, and the status information after participating in the first event. Send to device 300a. Instead of the location information of the event site 40, the identification information of the first event may be used. In response to this, the recommendation device 300a performs the status report registration process in the same manner as in FIG. 9 described above. That is, the user information 312 of the user U0 includes first state information before participation in the first event and second state information after participation in the first event.

Next, the recommendation device 300a selects the 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 position information included in the status report received in step S320, and from the event holding schedule (not shown) of the event venue 40 and the acquisition time of the status information included in the status report. Identify the first event. Then, the recommendation device 300a may select the user U0 from the identified participant list (not shown) of the first event.

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

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, the user terminal 100 displays the received index values before and after participation on the input/output unit 150 .

FIG. 15 is a diagram showing a display example of index values before and after participation according to the third embodiment. Here, an example is shown in which the user terminal 100 displays the state change summary screen 52 before and after participation in the event. State change summary screen 52 includes state changes 521 and 522 . The state change 521 is an example of comparing and displaying the daily average value before participation in the first event for the user U0 and the average value on the day of participation in the first event for a plurality of indices. For example, the first index is calorie consumption, 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 the stress level, which includes anxiety, tension, and friendliness. It shows that the anxiety level changed (decreased) from "5" before participation to "3" after participation. It shows that the degree of tension changed (decreased) from "4" before participation to "2" after participation. It shows that the degree of friendship changed (increased) from "3" before participation to "4" after participation. The state change 522 is a graphical representation of the transition of the total value of the stress level (total stress level) of the plurality of indicators (total stress level) for each hour of the day before and after participation in a graph for comparison. It should be noted that the higher the degree of anxiety and tension, the higher the total stress value, and the lower the degree of friendship, the higher the total stress value. In the state 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 the stress level of user U0 has decreased due to participation in the event. indicates that Note that when the recommendation device 300 detects a time or a time period in which the change in the stress value in the transition of the total stress level is larger than a predetermined value, the user terminal 100 updates the event or the like that the user participated in during the detected time period. It may be displayed on the change summary screen 52 .

Returning to Fig. 14, the explanation continues. 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, the user terminal 100 displays the received recommendation information on the input/output unit 150 as a recommendation screen.

FIG. 16 is a diagram showing a display example 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 guide information to the second participatory event as recommendation information. The second participatory event recommendation screen 53 includes recommendation information 531 and a participation application button 532 . The recommendation information 531 is an example showing, for example, the name of the participatory event to be recommended, the date and time of the event, an explanation, the target age group (participation condition), and the location of the event. Here, it is assumed that an event more suitable for the user U0 is determined as the recommendation information according to the state change (change in index value) of the user U0 before and after participating in the first event. When the participation application button 532 is pressed, a screen for inputting or selecting a participant name is displayed. User U0 can apply for and participate in the recommended event as described above.

Here, a specific example of recommending a second event based on changes in the user's state after experiencing the first event will be described. For example, when the stress value of the user U0 (before participating in the first event) is higher than a predetermined value, the recommendation device 300a performs the first recommendation process to perform the migration “experience” of a resort (first event). ) is determined as recommended information and recommended. Then, the recommendation device 300a acquires the state information after the emigration experience from the user U0. The state information after the migration experience (after participating in the event) includes vital data and the user's impression (satisfactory or dissatisfied) of the migration experience. The recommendation device 300a selects the health resort if the impression after the migration experience of the user U0 is satisfactory, or if the degree of stress value reduction (state change) calculated from the vital data before and after the migration experience is favorable. You may decide and recommend "permanent residence" to as the next recommendation information.

Alternatively, the recommendation device 300a may determine the recommendation information based on the personal information of the user U0 (for example, hometown or interests). For example, if the user U0 is from a rural area or likes nature, the recommendation device 300a determines and recommends an experience (for example, mountain climbing, first event) in an area rich in nature. At this time, the recommendation device 300a may adjust the difficulty level of mountain climbing in consideration of the health condition of the user. Then, the recommendation device 300a acquires state information after climbing from the user U0. If the user U0's post-climbing impression is satisfactory, or if the health condition such as vital data before and after climbing is good, the recommendation device 300a determines climbing another mountain as the next recommendation information, Recommendation to. On the other hand, if the user U0 is unsatisfied with the impression after climbing the mountain, the recommendation device 300a determines and recommends other experiences for people who like nature, such as experiences related to rivers and the sea, as the next recommendation information. good too. In addition, when the health condition and stress value of the user U0 such as vital data before and after mountain climbing are not good, the recommendation device 300a may determine and recommend mountain climbing with a lower difficulty level as the next recommendation information.

As described above, in the third embodiment, state information after experiencing the recommended event (activity, etc.), such as health condition and interests, is recorded (feedback). Then, based on the feedback, new recommendations are made, including the most suitable experiential events (experience learning, etc.). In addition, the recommendation information may include information such as medical examination at a medical institution. In that case, the health checkup result is included in the post-experience state information. In other words, it is possible to further recommend an optimal health checkup according to the accumulation of health checkup results and the like.

<Embodiment 4>
The fourth embodiment is a modification of the second embodiment described above. In the fourth embodiment, user's emotions and changes in emotions are grasped in real time, and recommended information is determined and provided according to the grasped contents. In particular, the recommendation device 300b according to the fourth embodiment may change the content of the presentation of the event being held according to the emotions of the users who are participating in the event and changes in their emotions.

FIG. 17 is a block diagram showing the overall configuration of a recommendation system 3000 according to the fourth embodiment. In the following description, the same reference numerals are given to the same configurations as those of the second embodiment, and illustration and detailed description thereof are omitted. A recommendation system 3000 is obtained by replacing the recommendation device 300 described above with a recommendation device 300b and adding an event operator device 500 . A second event is being held at the event venue 40, and the second event is, for example, a concert, a play, an attraction at a theme park, or the like. It is assumed that the second event is produced by the organizer of the event, that is, by staff U5 on the side of the operator, equipment, and the like. It shows that users U1 to U4 are participating in the second event. User U1 has a user terminal 100-1, user U2 has a user terminal 100-2, user U3 has a user terminal 100-3, and user U4 has a user terminal 100-4. User terminals 100-1 to 100-4 have the same functions as user terminal 100 described above.

The event operator device 500 is an example of the device on the operator side of the event described above, and is connected to the network N. The event operator device 500 is, for example, an information processing device such as a personal computer, a mobile phone terminal, a smart phone, or a tablet terminal. The event operator device 500 receives the recommendation information from the recommendation device 300b via the network N and displays it on the screen. Thereby, the staff member U5 can visually recognize the recommendation information through the recommendation device 300b. The recommendation information is, for example, information about the content of the presentation of the second event, user's emotion distribution for each area in the venue of the second event, and the like.

Alternatively, the event operator 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 .

The acquisition unit of the recommendation device 300b acquires status information from at least one of the users U1 to U4 participating in the second event. The determining unit of the recommendation device 300b determines recommended information based on the time or place when the status information was acquired from the user and the status information. The output unit of the recommendation device 300b outputs the determined recommendation information to the device on the side of the operator of the second event (event operator device 500) as an output destination. As a result, staff U5 on the side of the operator of the event can grasp the state (degree of excitement, degree of satisfaction), emotions, etc. of the participants of the second event. The output unit of the recommendation device 300b may output the determined recommendation information to any one of the user terminals 100-1 to 100-4, which is the acquisition source of the status information.

Furthermore, the determination unit of the recommendation device 300b may determine information regarding the content of the presentation of the second event as the recommendation information. Accordingly, it is possible to propose changes in the contents of the presentation to the staff U5 in real time according to the emotions of the participants of the second event. Note that the determination unit may include the reason for changing the effect content in the recommendation information. For example, the reason for changing the content of the presentation is to add a presentation using lighting since many users are enthusiastic. Also, the determination unit may include the effect content before change and the effect content after change in the recommendation information. Therefore, the staff member U5 can grasp the reason for changing the content of the proposed production and the content of the production before and after the change.

Furthermore, the output unit of the recommendation device 300b outputs an instruction to apply the effect content of the second event. As a result, the event operator device 500 can apply the effect contents of the second event to the effect device described above. Therefore, the presentation contents of the second event can be changed in real time according to the emotions of the participants.

Also, the acquisition unit of the recommendation device 300b may acquire state information at a plurality of points in time from users participating in the second event. In that case, the determination unit may derive a change in the user's state from the state information at each point in time, and determine the recommended information based on the derived state change. As a result, it is possible to realize a more effective presentation in accordance with changes in the emotions of the participants according to the progress of the second event, and to improve the satisfaction of the participants.

FIG. 18 is a flow chart showing the flow of the third recommendation process according to the fourth embodiment. As a premise, it is assumed that the above-described user registration processing and status reporting processing before participating in the second event have been completed for each of the users U1 to U4. However, it does not matter whether or not the second event to be held at the event venue 40 is recommended by the first recommendation processing described above. Assume that each of the users U1 to U4 is currently participating in at least the second event held at the event site 40 .

First, the recommendation device 300b performs a process of registering status reports at a plurality of times during participation in the second event (S320b). Specifically, while the user U1 is participating in the second event being held at the event venue 40, the user terminal 100-1 receives the information from the user U1 at a plurality of points in time by various means as described above. Get the status information of Then, as described above, the user terminal 100-1 sends a status report including the personal authentication information of the user U1, the location information of the event venue 40, and status information at a plurality of points in time during participation in the second event. It is transmitted to the recommendation device 300b via the network N. Instead of the location information of the event site 40, the identification information of the second event may be used. In response, the recommendation device 300b performs the process of registering status reports multiple times in the same manner as in FIG. 9 described above. In other words, the user information 312 of the user U1 includes status information at a plurality of times during participation in the second event.

Next, the recommendation device 300b selects the user U1 participating in the second event as a target user (S321b). For example, the recommendation device 300b identifies the event venue 40 from the position information included in the status report received in step S320b, and determines from the event holding schedule (not shown) of the event venue 40 and the acquisition time of the status information included in the status report. Identify a second event. Then, recommendation device 300b may select user U1 from the specified participant list (not shown) of the second event.

Then, the recommendation device 300b identifies, from the user information 312, the state information 3125 and the personal information 3122 at each point in time during the participation of the target user in the event (S332b). Subsequently, the recommendation device 300b analyzes the state information 3125 and the personal information 3122 at each time point during event participation, and derives changes in the state of the target user during event participation (S333b). For example, the recommendation device 300b detects whether the user U1 is excited or scared (with respect to the performance of the attraction) based on changes in heart rate, stress value, and the like during the second event.

Then, the recommendation device 300b determines recommendation information (event presentation) based on the derived state change (S334b). Then, the recommendation device 300b outputs the determined recommendation information to the event operator device 500 (S335b). In response, event operator device 500 displays the received recommendation information on input/output unit 150 . Then, the staff member U5 can determine, implement (instruct), etc. the change of the presentation in accordance with the change in the emotion of the user U1. Specifically, different effects may be performed depending on whether the heart rate of the user U1 is increased or decreased at a certain time of the event. For example, if the event is a horror event and it is detected that user U1's heart rate is not sufficiently high (he is not scared), an effect may be performed in which a ghost appears. At this time, the event operator device 500 may instruct the effect device to apply the changed content of the effect.

Also, the acquisition unit of the recommendation device 300b may acquire the status information of each of the plurality of users participating in the second event and the location information of each user. In this case, the determination unit analyzes each user's emotion from the state information, and determines the user's emotion distribution for each area in the venue of the second event as recommendation information based on the emotion and position information. The output unit then transmits the emotion distribution to the event operator device 500 . As a result, the user's emotion distribution (emotion map) for each region within the event venue 40 is displayed on the event operator device 500 . Therefore, the staff U5 can perform an appropriate effect for each area according to the emotion map. Also, 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. Thereby, the user terminal displays the user's emotion distribution for each area in the event site 40 on the screen. Therefore, the user can confirm a preferred area within the event venue 40, for example, a lively place or a calm place, and then head to that area. In addition, the output unit may transmit recommendation information such as emotion distribution to the user terminal of a user who intends to participate in the second event halfway through or a user who is outside the event venue 40 .

Furthermore, the determination unit of the recommendation device 300b may further determine the application location of the effect content based on the emotion distribution. In this case, the output unit designates the place of application and outputs an instruction to apply the effect content of the event. As a result, it is possible to automatically perform an appropriate effect for each area according to the emotion map.

FIG. 19 is a flow chart showing the flow of the fourth recommendation process according to the fourth embodiment. The premise is the same as in FIG. 18 described above.

First, the recommendation device 300b performs a process of registering status reports of a plurality of users participating in the second event (S320c). Specifically, while the 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 receives the above-described Status information is obtained from each of the users U1-U4 by various means. Then, as described above, each user terminal recommends, via the network N, a status report including the identity authentication information of each user, the location information of the event venue 40, and the status information during participation in the second event. Send to device 300b. Instead of the location information of the event site 40, the identification information of the second event may be used. In response to this, the recommendation device 300b performs the status report registration process of each user in the same manner as in FIG. 9 described above. That is, the user information 312 of each user includes state information during participation in the second event.

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

Then, the recommendation device 300b identifies the event participation state information 3125 and the personal information 3122 of the target user group from the user information 312 (S332c). Subsequently, the recommendation device 300b analyzes the state information 3125 during event participation and the personal information 3122 to derive the emotions of each user during event participation (S333c). Then, the recommendation device 300b determines recommendation information (emotion distribution) for each area in 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 whose position information is close to identify the emotions in each area. For example, the recommendation device 300b calculates the average value of the analysis results of the emotions of the users staying in each of the plurality of areas in the event venue 40, and identifies the emotion in the area corresponding to the average value. do. Similarly, the recommendation device 300b labels the identified emotions to the corresponding regions to generate an emotion distribution.

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

FIG. 20 is a diagram showing a display example of the emotion distribution 400 according to the fourth embodiment. Emotion distribution 400 indicates the analysis results of emotions of user groups in each of multiple areas 41 to 46 in event site 40 . For example, area 41 indicates "excitement", area 42 indicates "excitement", area 43 indicates "tension", area 44 indicates "joy", area 45 indicates "excitement", and area 46 indicates "depression". However, the emotion analysis results are not limited to these.

After that, the staff member U5 can check the emotion distribution 400 and decide and implement (instruct) changes in the presentation according to the change in the emotions of the user U1. For example, from the emotion distribution 400, the staff member U5 can visually ascertain where event participants are excited, where they are not excited, or where they are relaxed. Therefore, for example, when there are many users who are not enthusiastic in a certain area during a concert, which is the second event, the effect using lighting or the like may be changed for that area. In addition, an effect such as setting off fireworks may be applied in the vicinity of the exciting place (enthusiastic place). Alternatively, a relaxing effect may be applied to the excited area. In these cases, the event operator device 500 may instruct the effect device to apply the changed content of the effect.

Also, 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 due to the user's health condition, the recommendation device 300b may recommend that the user move to a relaxing area within the event venue 40 . Furthermore, the recommendation device 300b may use the state information of the user after the recommendation to make a recommendation again or change the effect content.

It should be noted that in S332b of FIG. 18 and S332c of FIG. 19 described above, the recommendation device 300b does not necessarily have to identify the personal information of the user participating in the event. In this case, in S332b and S332c, the recommendation device 300b analyzes the state at each time point during the participation in the event, and derives changes in the state and emotions of the target user during the event participation.

In addition, 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. In other words, the user may be able to confirm the above-described distribution of emotion, change in effect, reason for change in effect, and effect before and after change on the user terminal.

Here, the distribution of emotions in FIG. 20 described above is an example showing the distribution of emotions of each participant at the event venue at a certain point in time on a two-dimensional map. In addition, during the event, the recommendation device 300b may output changes in the distribution of emotion in chronological order to the event operator device 500 or the user terminals of users participating in the event. For example, the recommendation device 300b generates display information (for example, a pie chart) indicating the ratio of the number of users in the event hall as the emotion distribution. Then, the recommendation device 300b stores the generated display information in the storage unit 310 or the memory 320 in association with the acquisition time of the status information. Then, in a state in which two or more pieces of display information are held, the recommendation device 300b outputs so as to display changes in the distribution of emotions (display information) in chronological order.

For example, it is assumed that there is no change in the content of the production until 10 minutes after the start of the event, and that the number of participants showing boredom has increased. At this time, the recommendation device 300b determines the content of change, the reason for the change, the place of application, etc. of the effect content based on the emotional distribution 10 minutes after the start of the event. Then, the recommendation device 300b designates an application location and outputs an instruction to apply the effect content of the event. For example, the recommendation device 300b decides to change the effect, which was only lighting before the change of the event venue, to the effect of launching fireworks in order to increase the excitement level of the participants. At this time, the recommendation device 300b may designate an area with more users determined to be bored as the application location. The recommendation device 300b generates an emotion distribution according to the state report obtained and registered after the content of the presentation is changed (for example, 20 minutes after the start of the event). Then, recommendation device 300b displays changes in chronological order for the plurality of generated emotion distributions.

FIG. 21 is a diagram showing an example of changes in emotion distribution along a time series according to the fourth embodiment. A time transition 401 of the distribution of emotions indicates changes in the distribution of emotions of each user over time in the entire hall or in a partial area. Also, the temporal transition 401 of the emotion distribution indicates the transition of the temporal change of the emotion distribution from left to right. Specifically, the emotion distribution time transition 401 is an example of displaying an emotion distribution 410 at the start of the event, an emotion distribution 420 10 minutes after the event start, and an emotion distribution 430 20 minutes after the event start. The emotion distribution 410 indicates that the excitement 411, the joy 412, and the tension 413 are generally equal, and the pessimistic emotion is small, based on the expectation of each user for the event at the start. Here, it is assumed that the content of the presentation has not changed until 10 minutes after the start of the event. The emotion distribution 420 is the emotion distribution 10 minutes after the start of the event, and compared to the emotion distribution 410, excitement 421 and joy 422 decreased, tension 423 was generally maintained, and boredom 424 was added as a large percentage. is shown. The pre-change effect content 441 is text information indicating that the effect content was "lighting" 10 minutes after the start of the event. The emotion distribution 430 is the emotion distribution after 20 minutes from the start of the event, that is, after the above-described effect content is changed. Emotion distribution 430 shows a large percentage of extra enthusiasm 431 added, excitement 432 and joy 433 increased, and tension 434 and boredom 435 decreased when compared to emotion distribution 420 . The changed effect content 442 is text information indicating that the effect content has been changed to "fireworks launch" 20 minutes after the start of the event. The reason for change 443 is text information indicating the reason for the change from the effect content 441 before change to the effect content 442 after change. Here, the reason for change 443 indicates information that "many users in the relevant area were less excited". Note that the reason for the change may be "many users in the relevant area were very excited, so that they would be even more enthusiastic" (change was made to the effect of fireworks). Also, the temporal transition 401 of the distribution of emotions may be displayed on the event operator device 500 or another computer after the event as well as during the event. The time transition 401 of the emotion distribution may be displayed corresponding to each of the areas 41 to 46 described above. In that case, the emotion distribution may be displayed so that it can be easily compared for each area. Also, the emotion distribution for each area may be displayed in chronological order so that it can be easily compared. Also, the emotion distribution may be a distribution of average values of emotions corresponding to each of the areas 41-46. In other words, the average value of the analysis results of the emotions of multiple users who stay in each area may be displayed at a location corresponding to each area in the emotion distribution. At this time, the emotion distribution may be assigned a display size such as excitement 411 at a rate corresponding to the number of people staying in each area. Then, the user terminal should display the distribution of emotion for each of these areas and the transition over time. As a result, for example, the user can check the change in the distribution of emotions for each area displayed on his/her user terminal, and use this as an opportunity to move to a desired area during the event.

FIG. 22 is a diagram showing a display example of the contents of the effect 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 content of the presentation described above (fireworks launching) is performed near the left front area of the event venue 40 . Then, it is assumed that the recommendation screen 54 is displayed on the user terminal 100-1 possessed by the user U1 who is near the front left area of the event venue 40. FIG. The recommendation screen 54 includes performance contents 541 before and after the change and a change reason 542 . The effect content 541 before and after change includes the effect content 441 before change and the effect content 442 after change described above. Reason for change 542 is similar to reason for change 443 described above.

FIG. 23 is a diagram showing a display example of the emotion distribution 400a according to the fourth embodiment. The emotion distribution 400a is obtained by adding an effect change application location 47, effect contents 541 before and after the change, and a change reason 542 to the emotion distribution 400 of FIG.

In addition, the recommendation device 300b may utilize the results of the above-described emotion analysis (e.g., emotion distribution) for product sales and the like. For example, the recommendation device 300b may specify an enthusiastic area and instruct a van to sell goods or the like. This can contribute to the promotion of sales of goods to enthusiastic participants.

In addition, the recommendation device 300b may analyze information on changes in emotions and provide the analysis result to the event operator device 500. The analysis results may include timings and places (regions) in the event program where the participants were excited or relaxed. As a result, the event manager can utilize the analysis results in subsequent events planned. In addition, the recommendation device 300b may provide information to the user by posting analysis results, emotion distribution, etc. to an SNS (Social Networking Service) server.

<Other embodiments>
Note that the user described above may be a tourist who has visited a tourist spot. In that case, the recommendation device 300, 300a, or 300b (hereinafter referred to as the recommendation device 300 or the like) described above calculates the interest level of the tourist spot as an index value from the state information acquired from the user terminal of the tourist. You may provide the information which responded as recommendation information. For example, if the recommendation device 300 or the like is highly interested in a tourist resource such as a castle, the recommendation device 300 or the like may provide deeper information on the castle, or if the interest is low, the recommendation device 300 or the like may guide a change to another tourist resource. may The recommendation device 300 or the like may automatically make the change by the "voice guidance device", or may notify the tour conductor of the tourist's interest level and change the contents of the information provision at the discretion of the tour conductor. .

In addition, the user may input his or her own personal information (name, address, age, etc.), values, hobbies and preferences, desired conditions for spending holidays, etc. to the user terminal 100 . In this case, the user terminal 100 may transmit the input personal information or the like to the recommendation device 300 or the like, and the recommendation device 300 or the like may provide information to the user based on the received personal information or the like. . For example, the recommendation device 300 or the like may recommend information on a hospital, an event venue, or the like near the user's home.

Also, the recommendation device 300 and the like may provide the calculated index values (stress value, pain value) to the medical institution. For example, when a user undergoes online medical treatment, the recommendation device 300 or the like may provide a medical institution (doctor, etc.) or an event organization with the calculated stress value or pain value acquired from the user terminal. In addition, the results (underlying diseases, pre-existing diseases) obtained from online medical care may be used to determine who should be prioritized for evacuation in the event of a disaster.

Furthermore, the recommendation device 300 or the like may issue "local currency" to users who have participated in events or the like according to the recommendation information, or may request a local government or the like to issue "local currency". The local currency can contribute to the revitalization of the local economy.

In the second to fourth embodiments described above, the recommendation device 300 and the like and the authentication device 200 are 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 that 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.

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

It should be noted that the present disclosure is not limited to the above embodiments, and can be modified as appropriate without departing from the scope. In addition, the present disclosure may be implemented by appropriately combining each embodiment.

Some or all of the above embodiments may also be described in the following additional remarks, but are not limited to the following.
(Appendix A1)
Acquisition means for acquiring status information of a predetermined user;
determining means for determining recommended information based on the state information;
output means for outputting the determined recommendation information to a predetermined output destination;
recommendation device.
(Appendix A2)
The recommendation device according to appendix A1, wherein the determination unit determines participation guidance for a first event as the recommendation information.
(Appendix A3)
The recommendation device according to appendix A2, wherein the determination means determines the recommendation information based on the state information, further including guide information on products or services available when participating in the first event.
(Appendix A4)
The acquisition means acquires first state information of the user before participating in the first event and second state information of the user after participating in the first event,
The determining means derives a change in the state of the user from the first state information to the second state information, and determines the recommended information based on the derived state change. Appendix A2 or A3 The recommended device described in .
(Appendix A5)
The acquisition means acquires the state information from the user participating in the second event,
The determining means determines the recommended information based on the time or place at which the status information was obtained from the user and the status information;
The recommendation device according to any one of Appendices A1 to A4, wherein the output means outputs the determined recommendation information to a device on the side of the operator of the second event as the output destination.
(Appendix A6)
The recommendation device according to appendix A5, wherein the determination means determines information regarding the content of the presentation of the second event as the recommendation information.
(Appendix A7)
The recommendation device according to appendix A6, wherein the output means outputs an instruction to apply the effect content of the second event.
(Appendix A8)
The acquisition means acquires the state information and the position information of each user for each of the plurality of users participating in the second event,
The determining means analyzes the emotion of each user from the state information, and determines the user's emotion distribution for each area in the venue of the second event as the recommendation information based on the emotion and the position 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 recommendation device according to appendix A8, wherein the output means specifies the application location and outputs an instruction to apply the effect content of the event.
(Appendix A10)
The acquisition means acquires the state information at a plurality of points in time from the user participating in the second event,
According to any one of Appendices A5 to A9, the determining means derives a change in the state of the user from the state information at each point in time, and determines the recommended information based on the derived state change. Recommended device.
(Appendix A11)
The acquisition means acquires a status report including the status information from a user terminal owned by the user,
The recommendation device further includes registration means for registering the state information and the user in association with each other,
The recommendation device according to any one of appendices A1 to A10, wherein the determination means determines the recommendation information using one or more of the state information associated with the user at a predetermined timing.
(Appendix A12)
The registration means pre-registers personal authentication information for registration of the user,
the status report includes authentication information for authentication of the user;
Further comprising identifying means for identifying the user related to the status report by authentication using the personal authentication information for registration and authentication,
The recommendation device according to appendix A11, wherein the registration unit registers the state information included in the state report in association with the identified user.
(Appendix A13)
The determining means is
analyzing the state information to calculate an index value indicating the state of the user;
The recommendation device according to any one of Appendixes A1 to A12, wherein the recommendation information is determined using the index value.
(Appendix A14)
The condition information includes at least one of vital data measured from the user and gait of the user detected by a detection device embedded in an insole worn by the user. The recommended device described in .
(Appendix A15)
The acquisition means further acquires personal information of the user,
The recommendation device according to any one of Appendixes A1 to A14, wherein the determination means determines the recommendation information based on the state information and the personal information.
(Appendix B1)
a user terminal possessed by a predetermined user;
a recommendation device;
The recommendation device is
Acquisition means for acquiring the state information of the user from the user terminal;
determining means for determining recommended information based on the state information;
output means for outputting the determined recommendation information to a predetermined output destination;
A recommender system.
(Appendix B2)
The recommendation system according to appendix B1, wherein the determination unit determines participation guidance for a first event as the recommendation information.
(Appendix C1)
the computer
obtaining state information for a given user;
determining recommendation information based on the state information;
A recommendation method for outputting the determined recommendation information to a predetermined output destination.
(Appendix D1)
an acquisition process for acquiring status information of a given user;
a determination process for determining recommended 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 recommended program that causes a computer to execute

Although the present invention has been described with reference to the embodiments (and examples), the present invention is not limited to the above-described embodiments (and examples). Various changes 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.

1 recommendation device 11 acquisition unit 12 determination unit 13 output unit 1000 recommendation system 2000 recommendation system 3000 recommendation system N network U0 user U1 user U2 user U3 user U4 user U5 staff 100 user terminal 100-1 user terminal 100-2 user terminal 100- 3 User terminal 100-4 User terminal 110 Camera 120 Storage unit 121 Program 122 Location information 123 Personal authentication information 130 Memory 140 Communication unit 150 Input/output unit 160 Control unit 161 Registration unit 162 Acquisition unit 163 Display control unit 200 Authentication device 210 Face information database
211 User ID
212 facial feature information 220 face detection unit 230 feature point extraction unit 240 registration unit 250 authentication unit 300 recommendation device 300a recommendation device 300b recommendation device 310 storage unit 311 program 312 user information 3121 user ID
3122 personal information 3123 terminal information 3124 position information 3125 state information 3126 index value 3127 recommendation history 320 memory 330 communication unit 340 control unit 341 acquisition unit 342 registration unit 343 authentication control unit 344 determination unit 345 output unit 40 event venue 400 emotion distribution 400a emotion Distribution 41 Area 42 Area 43 Area 44 Area 45 Area 46 Area 47 Applied place of production change 401 Emotion distribution time transition 410 Emotion distribution 411 Excitement 412 Joy 413 Tension 420 Emotion distribution 421 Excitement 422 Joy 423 Tension 424 Boredom 430 Emotion distribution 431 Large Enthusiasm 432 Excitement 433 Joy 434 Tension 435 Boredom 441 Production content before change 442 Production content after change 443 Reason for change 500 Event operator device 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 Contents of production before and after change 542 Reason for change

Claims (19)

1. Acquisition means for acquiring status information of a predetermined user;
   determining means for determining recommended information based on the state information;
   output means for outputting the determined recommendation information to a predetermined output destination;
   recommendation device.
2. 2. The recommendation device according to claim 1, wherein said determination means determines participation guidance for a first event as said recommendation information.
3. 3. The recommendation device according to claim 2, wherein said determination means determines said recommendation information further including guide information of products or services available when participating in said first event, based on said state information.
4. The acquisition means acquires first state information of the user before participating in the first event and second state information of the user after participating in the first event,
   3. The determining means derives a change in the state of the user from the first state information to the second state information, and determines the recommended information based on the derived state change. 4. The recommendation device according to 3.
5. The acquisition means acquires the state information from the user participating in the second event,
   The determining means determines the recommended information based on the time or place at which the status information was obtained from the user and the status information;
   5. The recommendation device according to any one of claims 1 to 4, wherein the output means outputs the determined recommendation information to a device on the side of the operator of the second event as the output destination.
6. 6. The recommendation device according to claim 5, wherein said determination means determines information regarding the content of presentation of said second event as said recommendation information.
7. 7. The recommendation device according to claim 6, wherein said output means outputs an instruction to apply the effect content of said second event.
8. The acquisition means acquires the state information and the position information of each user for each of the plurality of users participating in the second event,
   The determining means analyzes the emotion of each user from the state information, and determines the user's emotion distribution for each area in the venue of the second event as the recommendation information based on the emotion and the position information. A recommendation device according to any one of claims 5 to 7.
9. The determining means further determines an application location of the effect content based on the emotion distribution,
   9. The recommendation device according to claim 8, wherein said output means designates said place of application and outputs an instruction to apply the effect content of said event.
10. The acquisition means acquires the state information at a plurality of points in time from the user participating in the second event,
    10. The determining unit according to any one of claims 5 to 9, wherein the determining means derives changes in the state of the user from the state information at each point in time, and determines the recommended information based on the derived changes in the state. recommended equipment.
11. The acquisition means acquires a status report including the status information from a user terminal owned by the user,
    The recommendation device further includes registration means for registering the state information and the user in association with each other,
    The recommendation device according to any one of claims 1 to 10, wherein the determination means determines the recommendation information at a predetermined timing using one or more pieces of the state information associated with the user.
12. The registration means pre-registers personal authentication information for registration of the user,
    the status report includes authentication information for authentication of the user;
    Further comprising identifying means for identifying the user related to the status report by authentication using the personal authentication information for registration and authentication,
    The recommendation device according to claim 11, wherein the registration unit registers the state information included in the state report in association with the specified user.
13. The determining means is
    analyzing the state information to calculate an index value indicating the state of the user;
    The recommendation device according to any one of claims 1 to 12, wherein the recommendation information is determined using the index value.
14. 14. The state information includes at least one of vital data measured from the user and gait of the user detected by a detection device embedded in an insole worn by the user. Recommended device according to paragraph.
15. The acquisition means further acquires personal information of the user,
    The recommendation device according to any one of claims 1 to 14, wherein the determination means determines the recommendation information based on the state information and the personal information.
16. a user terminal possessed by a predetermined user;
    a recommendation device;
    The recommendation device is
    Acquisition means for acquiring the state information of the user from the user terminal;
    determining means for determining recommended information based on the state information;
    output means for outputting the determined recommendation information to a predetermined output destination;
    A recommender system.
17. 17. The recommendation system according to claim 16, wherein said determination means determines participation guidance for a first event as said recommendation information.
18. the computer
    obtaining state information for a given user;
    determining recommendation information based on the state information;
    A recommendation method for outputting the determined recommendation information to a predetermined output destination.
19. an acquisition process for acquiring status information of a given user;
    a determination process for determining recommended 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 recommended program that causes a computer to execute

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