Information processing device, providing method, and providing program

Abstract

To recognize whether or not the action performed by a user is useful.SOLUTION: An information processing device 100 includes: an acquisition unit 120 which acquires schedule information being information indicating the schedule of a user and biological information of the user; an action prediction unit 130 which predicts the future action of the user by using the schedule information; a biology prediction unit 140 which predicts future biological information of the user on the basis of the action prediction information indicating the future action of the user and the biological information; a control unit 150 which determines whether or not the action indicated by the action prediction information is useful for the user by using the action prediction information and the biology prediction information being the future biological information of the user; and an output unit 160 which outputs information indicating whether or not the action indicated by the action prediction information is useful for the user.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, a providing method, and a providing program. [Background technology]

[0002] In recent years, exercise is recommended for health. A technology for providing advice has been proposed (see Patent Document 1). The exercise support system of Patent Document 1 calculates a first contribution rate indicating the degree of influence of second biometric data on first biometric data. The exercise support system calculates a second contribution rate indicating the degree of influence of exercise record data on second biometric data. The exercise support system calculates a third contribution rate indicating the degree of influence of exercise record data on the first biometric data based on the first contribution rate and the second contribution rate. The exercise support system generates a ranking in which the exercise record data is ranked in descending order of the third contribution rate. The exercise support system generates advice for improving the health of a subject based on the ranking. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6719942 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when a user performs a certain action in the future, there is a problem that the user cannot judge whether the action is useful or not.

[0005] The purpose of the present disclosure is to allow users to recognize whether the actions they perform are useful or not. [Means for solving the problem]

[0006] An information processing device according to one aspect of the present disclosure is provided. The information processing device includes an acquisition unit that acquires schedule information, which is information indicating a schedule of a user, and biometric information of the user, an action prediction unit that predicts a future action of the user using the schedule information, a biometric prediction unit that predicts future biometric information of the user based on the action prediction information indicating the future action of the user and the biometric information, a control unit that uses the action prediction information and biometric prediction information, which is the future biometric information of the user, to determine whether it is useful for the user to perform the action indicated by the action prediction information, and an output unit that outputs information indicating whether it is useful for the user to perform the action indicated by the action prediction information. Effect of the Invention

[0007] According to the present disclosure, it is possible to allow a user to recognize whether an action he or she takes is useful or not. [Brief description of the drawings]

[0008] [Figure 1] FIG. 2 is a diagram illustrating hardware included in an information processing device. [Diagram 2] FIG. 2 is a block diagram showing functions of the information processing device. [Diagram 3] 11 is a flowchart illustrating an example of a process executed by an information processing device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment will be described with reference to the drawings. The following embodiment is merely an example, and various modifications are possible within the scope of the present disclosure.

[0010] Embodiment 1 is a diagram showing hardware included in an information processing device. The information processing device 100 is a computer. For example, the information processing device 100 is a personal computer (PC), a smartphone, a tablet terminal, a server, etc. The information processing device 100 is a device that executes a providing method. The information processing device 100 includes a processor 101 , a volatile storage device 102 , and a non-volatile storage device 103 .

[0011] The processor 101 controls the entire information processing device 100. For example, the processor 101 is a central processing unit (CPU) or a field programmable gate array (FPGA). The processor 101 may be a multiprocessor. The information processing device 100 may also include a processing circuit.

[0012] The volatile storage device 102 is a main storage device of the information processing device 100. For example, the volatile storage device 102 is a random access memory (RAM). The non-volatile storage device 103 is an auxiliary storage device of the information processing device 100. For example, the non-volatile storage device 103 is a hard disk drive (HDD) or a solid state drive (SSD).

[0013] Next, functions of the information processing device 100 will be described. 2 is a block diagram showing the functions of the information processing device 100. The information processing device 100 includes a storage unit 110, an acquisition unit 120, a behavior prediction unit 130, a biological prediction unit 140, a control unit 150, and an output unit 160.

[0014] The storage unit 110 may be realized as a storage area secured in the volatile storage device 102 or the non-volatile storage device 103 . A part or all of the acquisition unit 120, the behavior prediction unit 130, the biological prediction unit 140, the control unit 150, and the output unit 160 may be realized by a processing circuit. Also, a part or all of the acquisition unit 120, the behavior prediction unit 130, the biological prediction unit 140, the control unit 150, and the output unit 160 may be realized as a module of a program executed by the processor 101. For example, the program executed by the processor 101 is also called a providing program. For example, the providing program is recorded on a recording medium.

[0015] The storage unit 110 stores various information. The acquisition unit 120 acquires schedule information. For example, the acquisition unit 120 acquires schedule information from a schedule book stored in the storage unit 110. Also, for example, the acquisition unit 120 acquires schedule information by an input operation by the user. The schedule information is information indicating a schedule of the user. The schedule information may be information indicating a schedule for exercise. Also, the schedule information may be information indicating a schedule other than exercise. For example, the schedule information indicates a schedule for a meeting.

[0016] The acquisition unit 120 may acquire location information of the user (i.e., the user's current location). For example, the acquisition unit 120 acquires the location information from a GPS (Global Positioning System). Also, for example, the acquisition unit 120 acquires the location information by an input operation by the user. Also, for example, the acquisition unit 120 acquires the location information wirelessly. Note that the location information is represented by, for example, latitude, longitude, and altitude.

[0017] When the location information is acquired, the acquisition unit 120 acquires weather information for the location indicated by the location information. For example, the acquisition unit 120 acquires weather information from a website that publishes weather information for the location. Also, for example, the acquisition unit 120 acquires weather information by a user's input operation. Note that the weather information includes the current weather, future weather, temperature, humidity, etc. Weather includes sunny, rainy, snowy, thunder, etc.

[0018] When the location information is acquired, the acquisition unit 120 acquires map information. For example, the acquisition unit 120 acquires the map information from the storage unit 110. Also, for example, the acquisition unit 120 acquires the map information from an external device. Note that the external device is a device that exists outside the information processing device 100. For example, the external device is a cloud server. Note that the illustration of the external device is omitted.

[0019] The behavior prediction unit 130 predicts the user's future behavior using the schedule information. The prediction process will be described using a specific example. For example, the schedule information indicates that the user will run a marathon for 30 minutes. Therefore, the behavior prediction unit 130 predicts that the user will run a marathon for 30 minutes.

[0020] The behavior prediction unit 130 may predict the user's future behavior using schedule information, location information, weather information, and map information. The prediction process will be described using a specific example. For example, the schedule information indicates that a meeting will be held at point A. The behavior prediction unit 130 searches for a route from the user's current location to point A using the schedule information, location information, weather information, and map information. For example, when the weather information indicates "sunny", the behavior prediction unit 130 searches for the shortest route. For example, when the weather information indicates "rain", the behavior prediction unit 130 searches for a route that avoids the rain. The behavior prediction unit 130 may search for a route using a conventional technique. The behavior prediction unit 130 may search for a route using a database constructed based on past behavior information of a large number of users. The behavior prediction unit 130 calculates the time it takes the user to walk to point A. For example, the behavior prediction unit 130 calculates the travel time based on the user's walking speed and the route. The user's walking speed may be stored in the storage unit 110. The acquisition unit 120 may also acquire the walking speed of the user through an input operation by the user. The behavior prediction unit 130 may calculate a travel time based on a general walking speed and a route. As a result, for example, a travel time of "30 minutes" is calculated. Therefore, the behavior prediction unit 130 predicts that the user will walk for 30 minutes.

[0021] Also, when the schedule information indicates that a meeting will be held at point A and that the means of transportation are walking and train, the behavior prediction unit 130 calculates only the walking travel time.

[0022] The behavior prediction unit 130 may not predict one behavior. That is, the behavior prediction unit 130 may predict multiple behaviors of the user using schedule information. The behavior prediction unit 130 may also predict multiple behaviors of the user using schedule information, location information, weather information, and map information.

[0023] After completing the prediction process, the behavior prediction unit 130 outputs behavior prediction information indicating the future behavior of the user.

[0024] The acquisition unit 120 acquires biometric information of a user. For example, the acquisition unit 120 acquires the biometric information by an input operation of the user. Also, for example, the acquisition unit 120 acquires the biometric information from a device worn by the user. Note that, for example, the biometric information is information that indicates the mental and physical state of the user, such as heart rate, body temperature, and fatigue level.

[0025] The biometric prediction unit 140 predicts the biometric information of a future user based on the behavior prediction information and the biometric information. For example, the biometric prediction unit 140 searches for information similar to the behavior prediction information and the biometric information from big data to perform the prediction. Also, for example, the biometric prediction unit 140 performs the prediction using a database. Also, for example, the biometric prediction unit 140 performs the prediction using a trained model. In detail, when the biometric prediction unit 140 inputs the behavior prediction information and the biometric information into the trained model, the trained model outputs the biometric information of the future user. The biometric prediction unit 140 predicts the output information as the biometric information of the future user.

[0026] Here, the acquisition unit 120 may acquire past behavioral information of the user. For example, the acquisition unit 120 acquires the past behavioral information from the storage unit 110 or an external device. Also, for example, the acquisition unit 120 acquires the past behavioral information by an input operation of the user. Note that, for example, the past behavioral information indicates drinking. Also, for example, the past behavioral information may include the date and time of the activity and the amount of alcohol consumed.

[0027] The biological prediction unit 140 may predict the future biological information of the user based on the behavior prediction information, the biological information, and the past behavior information. For example, if the past behavior information indicates drinking, the biological prediction unit 140 predicts the future biological information of the user taking drinking into consideration. As described above, the biological prediction unit 140 performs prediction using big data, a database, a trained model, and the like. The biological prediction unit 140 can improve prediction accuracy by using the past behavior information. For example, if a user drank a large amount of alcohol at a social gathering the day before, the user's drinking behavior significantly affects the user's condition the next day. Therefore, the biological prediction unit 140 can improve prediction accuracy by using the past behavior information (e.g., drinking).

[0028] After the prediction process is completed, the biological prediction unit 140 outputs biological prediction information. Note that the biological prediction information is biological information of a future user.

[0029] The control unit 150 uses the behavior prediction information and the biological prediction information to determine whether it is useful for the user to perform the behavior indicated by the behavior prediction information. For example, the control unit 150 uses the behavior prediction information and the biological prediction information, and the determination information indicating the correspondence between the behavior prediction information, the biological prediction information, and the usefulness, and the behavior prediction information and the biological prediction information to determine whether it is useful for the user to perform the behavior indicated by the behavior prediction information. In addition, the control unit 150 uses the behavior prediction information, the biological prediction information, and the trained model to determine whether it is useful for the user to perform the behavior indicated by the behavior prediction information. In detail, when the control unit 150 inputs the behavior prediction information and the biological prediction information to the trained model, the trained model outputs information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information.

[0030] The output unit 160 outputs information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information. For example, the output unit 160 outputs the information to a display of the information processing device 100. Also, for example, the output unit 160 outputs the information to a terminal used by the user. Specifically, when the information processing device 100 is a server, the output unit 160 outputs the information to a smartphone used by the user.

[0031] By visually checking the information, the user can recognize whether or not the action that the user will take in the future will be useful.

[0032] Next, the process executed by the information processing device 100 will be described with reference to a flowchart. Fig. 3 is a flowchart showing an example of processing executed by the information processing device. In the processing in Fig. 3, the acquisition unit 120 acquires schedule information, user position information, weather information, map information, user biometric information, and user past behavior information. (Step S11) The acquisition unit 120 acquires schedule information, user location information, weather information, map information, user biometric information, and user past behavior information. (Step S12) The behavior prediction unit 130 predicts the behavior of the user by using the schedule information, the location information, the weather information, and the map information, thereby enabling the information processing device 100 to obtain behavior prediction information. (Step S13) The biological prediction unit 140 predicts future biological information of the user based on the behavior prediction information, the biological information, and the past behavior information. In this way, the information processing device 100 can obtain biological prediction information. (Step S14) The control unit 150 uses the behavior prediction information and the biological prediction information to determine whether it is useful for the user to perform the behavior indicated by the behavior prediction information. (Step S15) The output unit 160 outputs information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information.

[0033] According to the embodiment, the information processing device 100 outputs information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information. Therefore, the user can recognize whether the behavior performed by the user is useful. Therefore, the information processing device 100 can allow the user to recognize whether the behavior performed by the user is useful.

[0034] The control unit 150 may use the behavior prediction information and the biological prediction information to determine the usefulness of the user performing the behavior indicated by the behavior prediction information. For example, the control unit 150 determines the usefulness using usefulness determination information indicating the correspondence between the behavior prediction information, the biological prediction information, and the usefulness, the behavior prediction information, and the biological prediction information. The control unit 150 also determines the usefulness using the behavior prediction information, the biological prediction information, and the trained model. In detail, when the control unit 150 inputs the behavior prediction information and the biological prediction information to the trained model, the trained model outputs the usefulness. The usefulness may be expressed by a degree (e.g., high, low, etc.) or may be expressed by a numerical value.

[0035] The output unit 160 outputs the usefulness. For example, the output unit 160 outputs the usefulness to a display of the information processing device 100. The user can recognize the usefulness of the action performed by the user by visually checking the usefulness.

[0036] Furthermore, the information processing device 100 may execute the following process. The acquisition unit 120 acquires the calorie consumption desired by the user and the fatigue level desired by the user. For example, the acquisition unit 120 acquires the calorie consumption and the fatigue level from the storage unit 110 or an external device. Also, for example, the acquisition unit 120 acquires the calorie consumption and the fatigue level through an input operation by the user.

[0037] The control unit 150 uses the behavior prediction information to determine the calories consumed when the user performs the behavior indicated by the behavior prediction information (hereinafter, the predicted calories consumed). For example, the control unit 150 performs multiple regression analysis using the type of exercise and exercise time indicated by the behavior prediction information as input variables and the predicted calories consumed as the objective variable. This determines the predicted calories consumed. Also, for example, the control unit 150 determines the predicted calories consumed based on the calorie consumption information indicating the correspondence between the type of exercise, exercise time, and calories consumed, and the behavior prediction information. Also, for example, the control unit 150 determines the predicted calories consumed using the behavior prediction information and the learned model.

[0038] The control unit 150 uses the behavior prediction information and the biological prediction information to determine the fatigue level when the user performs the behavior indicated by the behavior prediction information (hereinafter, the predicted fatigue level). For example, the control unit 150 performs multiple regression analysis using the type of exercise and exercise time indicated by the behavior prediction information and the biological prediction information as input variables and the predicted fatigue level as an objective variable. This determines the predicted fatigue level. Also, for example, the control unit 150 determines the predicted fatigue level using the behavior prediction information, the biological prediction information, and the learned model.

[0039] The control unit 150 compares the calorie consumption and fatigue level acquired by the acquisition unit 120 with the predicted calorie consumption and predicted fatigue level, and calculates the degree of agreement.

[0040] The output unit 160 outputs the degree of match. For example, the output unit 160 outputs the degree of match to a display of the information processing device 100. By visually checking the degree of match, the user can recognize whether or not the action performed by the user is desired by the user.

[0041] Furthermore, the information processing device 100 may execute the following process. The acquisition unit 120 acquires the calorie consumption desired by the user, the fatigue level desired by the user, and the safety level of the exercise desired by the user. For example, the acquisition unit 120 acquires the calorie consumption, fatigue level, and safety level of the exercise from the storage unit 110 or an external device. Also, for example, the acquisition unit 120 acquires the calorie consumption, fatigue level, and safety level of the exercise by an input operation by the user. The safety level of the exercise indicates the degree of safety for the exercise. The safety level of the exercise is represented by the type of exercise and the safety level. The safety level of the exercise is an indicator of muscle damage, heat stroke, etc. due to exercise.

[0042] The control unit 150 uses the behavior prediction information to determine the safety of the exercise and the predicted calorie consumption. For example, the control unit 150 performs multiple regression analysis using the type of exercise and exercise time indicated by the behavior prediction information as input variables and the safety of the exercise and the predicted calorie consumption as objective variables. This determines the safety of the exercise and the predicted calorie consumption. Also, for example, the control unit 150 uses the behavior prediction information and the learned model to determine the safety of the exercise and the predicted calorie consumption. The control unit 150 uses the behavior prediction information and the biological prediction information to determine the predicted fatigue level.

[0043] The control unit 150 compares the calorie consumption, fatigue level, and safety level of the exercise acquired by the acquisition unit 120 with the predicted calorie consumption, predicted fatigue level, and determined safety level of the exercise, and calculates the degree of agreement. The output unit 160 outputs the degree of match. By visually checking the degree of match, the user can recognize whether the action being performed by the user is the one desired by the user.

[0044] Furthermore, when the behavior prediction information indicates a plurality of behaviors, the control unit 150 determines the predicted calorie consumption and predicted fatigue level corresponding to each of the plurality of behaviors. The control unit 150 compares the predicted calorie consumption and predicted fatigue level corresponding to each of the plurality of behaviors with the calorie consumption and fatigue level acquired by the acquisition unit 120, and calculates the degree of agreement between them. In this way, the multiple degrees of agreement are calculated. The output unit 160 outputs the multiple degrees of agreement. Furthermore, the output unit 160 may output the multiple degrees of agreement in ascending or descending order, and may output the plurality of behaviors corresponding to the multiple degrees of agreement.

[0045] Furthermore, the following supplementary notes are disclosed regarding the embodiments. (Appendix 1) An acquisition unit that acquires schedule information that is information indicating a schedule of a user and biological information of the user; A behavior prediction unit that predicts a future behavior of the user by using the schedule information; a biometric prediction unit that predicts future biometric information of the user based on behavior prediction information indicating future behavior of the user and the biometric information; a control unit that uses the behavior prediction information and future biometric prediction information of the user to determine whether it is useful for the user to perform a behavior indicated by the behavior prediction information; an output unit that outputs information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information; An information processing device having the above configuration. (Appendix 2) The acquisition unit acquires location information of the user, meteorological information about a location indicated by the location information, and map information, The behavior prediction unit predicts a future behavior of the user by using the schedule information, the location information, the weather information, and the map information. 2. An information processing device according to claim 1. (Appendix 3) The acquisition unit acquires past behavior information of the user, The biological prediction unit predicts future biological information of the user based on the behavior prediction information, the biological information, and the past behavior information. 3. The information processing device according to claim 1 or 2. (Appendix 4) The control unit determines a usefulness of the user performing a behavior indicated by the behavior prediction information by using the behavior prediction information and the biological prediction information; The output unit outputs the usefulness. 4. An information processing device according to claim 1. (Appendix 5) The acquisition unit acquires a calorie consumption level desired by the user and a fatigue level desired by the user, the control unit uses the behavior prediction information to determine a predicted calorie consumption which is the calorie consumption when the user performs the behavior indicated by the behavior prediction information, uses the behavior prediction information and the biological prediction information to determine a predicted fatigue level which is the fatigue level when the user performs the behavior indicated by the behavior prediction information, compares the calorie consumption and the fatigue level, and compares the predicted calorie consumption and the predicted fatigue level to calculate a degree of agreement; The output unit outputs the degree of match. 5. An information processing device according to any one of claims 1 to 4. (Appendix 6) The acquisition unit acquires a calorie consumption level desired by the user, a fatigue level desired by the user, and a safety level of the exercise desired by the user, the control unit uses the behavior prediction information to determine a predicted calorie consumption, which is the calorie consumption when the user performs the behavior indicated by the behavior prediction information, and a safety level of the exercise; uses the behavior prediction information and the biological prediction information to determine a predicted fatigue level, which is the fatigue level when the user performs the behavior indicated by the behavior prediction information; compares the calorie consumption, the fatigue level, and the acquired safety level of the exercise with the predicted calorie consumption, the predicted fatigue level, and the determined safety level of the exercise, and calculates a degree of agreement; The output unit outputs the degree of match. 5. An information processing device according to any one of claims 1 to 4. (Appendix 7) An information processing device, Acquire schedule information which is information indicating a schedule of a user and biometric information of the user; Using the schedule information, predict future actions of the user; predicting future biometric information of the user based on behavior prediction information indicating future behavior of the user and the biometric information; Using the behavior prediction information and future biometric prediction information of the user, it is determined whether it is useful for the user to perform the behavior indicated by the behavior prediction information; outputting information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information; How it is provided. (Appendix 8) On the computer, Acquire schedule information which is information indicating a schedule of a user and biometric information of the user; Using the schedule information, predict future actions of the user; predicting future biometric information of the user based on behavior prediction information indicating future behavior of the user and the biometric information; Using the behavior prediction information and future biometric prediction information of the user, it is determined whether it is useful for the user to perform the behavior indicated by the behavior prediction information; outputting information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information; The provided program that executes the process. [Explanation of symbols]

[0046] 100 information processing device, 101 processor, 102 volatile storage device, 103 non-volatile storage device, 110 storage unit, 120 acquisition unit, 130 behavior prediction unit, 140 biological prediction unit, 150 control unit, 160 output unit.

Claims

1. An acquisition unit that acquires schedule information that is information indicating a schedule of a user and biological information of the user; A behavior prediction unit that predicts a future behavior of the user by using the schedule information; a biometric prediction unit that predicts future biometric information of the user based on behavior prediction information indicating future behavior of the user and the biometric information; a control unit that uses the behavior prediction information and future biometric prediction information of the user to determine whether it is useful for the user to perform a behavior indicated by the behavior prediction information; an output unit that outputs information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information; An information processing device having the above configuration.

2. The acquisition unit acquires location information of the user, meteorological information about a location indicated by the location information, and map information, The behavior prediction unit predicts a future behavior of the user by using the schedule information, the location information, the weather information, and the map information. The information processing device according to claim 1 .

3. The acquisition unit acquires past behavior information of the user, The biological prediction unit predicts future biological information of the user based on the behavior prediction information, the biological information, and the past behavior information.

3. The information processing device according to claim 1 or 2.

4. The control unit determines a usefulness of the user performing a behavior indicated by the behavior prediction information by using the behavior prediction information and the biological prediction information; The output unit outputs the usefulness.

3. The information processing device according to claim 1 or 2.

5. The acquisition unit acquires a calorie consumption level desired by the user and a fatigue level desired by the user, the control unit uses the behavior prediction information to determine a predicted calorie consumption which is the calorie consumption when the user performs the behavior indicated by the behavior prediction information, uses the behavior prediction information and the biological prediction information to determine a predicted fatigue level which is the fatigue level when the user performs the behavior indicated by the behavior prediction information, compares the calorie consumption and the fatigue level, and compares the predicted calorie consumption and the predicted fatigue level to calculate a degree of agreement; The output unit outputs the degree of match.

3. The information processing device according to claim 1 or 2.

6. The acquisition unit acquires a calorie consumption level desired by the user, a fatigue level desired by the user, and a safety level of the exercise desired by the user, the control unit uses the behavior prediction information to determine a predicted calorie consumption, which is the calorie consumption when the user performs the behavior indicated by the behavior prediction information, and a safety level of the exercise; uses the behavior prediction information and the biological prediction information to determine a predicted fatigue level, which is the fatigue level when the user performs the behavior indicated by the behavior prediction information; compares the calorie consumption, the fatigue level, and the acquired safety level of the exercise with the predicted calorie consumption, the predicted fatigue level, and the determined safety level of the exercise, and calculates a degree of agreement; The output unit outputs the degree of match.

3. The information processing device according to claim 1 or 2.

7. An information processing device, Acquire schedule information which is information indicating a schedule of a user and biometric information of the user; Using the schedule information, predict future actions of the user; predicting future biometric information of the user based on behavior prediction information indicating future behavior of the user and the biometric information; Using the behavior prediction information and future biometric prediction information of the user, it is determined whether it is useful for the user to perform the behavior indicated by the behavior prediction information; outputting information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information; How it is provided.

8. On the computer, Acquire schedule information which is information indicating a schedule of a user and biometric information of the user; Using the schedule information, predict future actions of the user; predicting future biometric information of the user based on behavior prediction information indicating future behavior of the user and the biometric information; Using the behavior prediction information and future biometric prediction information of the user, it is determined whether it is useful for the user to perform the behavior indicated by the behavior prediction information; outputting information indicating whether it is useful for the user to perform the behavior indicated by the behavior prediction information; The provided program that executes the process.

Images