Information processing device, information processing method, and information processing program

Abstract

To obtain questionnaire results that reflect the individual characteristics of the subjects. [Solution] When the server 14 presents the user with multiple questions used in a questionnaire to investigate the user's individuality, it displays a screen on the user terminal's display unit that allows the user to answer the questions using sequential values. The server 14 then acquires the sequential values ​​representing the answers entered by the user operating the user terminal and stores these sequential values ​​in a storage unit.

Description

Technical Field

[0001] The disclosed technology relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Patent Document 1 discloses a counseling apparatus that allows respondents to freely express their own emotions, simplifies the aggregation and analysis thereof, and can grasp the subjective emotions and stress of the respondents.

[0003] Patent Document 2 discloses a technology that, in counseling using the SAT method, appropriately extracts subjects who need to receive additional counseling based on the results of counseling by a computer system, and gives the subjects an opportunity to receive appropriate psychotherapy.

[0004] Patent Document 3 discloses a system that provides an appropriate mental healthcare service without requiring the temporal and mental burden of hospital visits.

[0005] Patent Document 4 discloses a technology that can be easily used during periods of increased stress or in free time, while providing an environment that facilitates the provision of counseling services by mental health professionals.

[0006] Patent Document 5 discloses providing a quick-reference booklet for personality diagnosis that can further improve the accuracy of personality diagnosis using an egogram and allow users to easily learn methods for improving negative factors.

[0007] Patent Document 6 discloses a technology that takes accurate and clear achievement of personality judgment using an egogram as its technical problem, and thereby obtains accurate and highly reliable personality judgment using an egogram.

Prior Art Documents

Patent Documents

[0008] [Patent Document 1] Patent No. 4871214 [Patent Document 2] Patent No. 4960766 [Patent Document 3] Japanese Patent Publication No. 2005-334205 [Patent Document 4] Japanese Patent Publication No. 2003-108674 [Patent Document 5] Utility Model Registration No. 3220569 Gazette [Patent Document 6] Japanese Patent Application Publication No. 07-231886 [Overview of the project] [Problems that the invention aims to solve]

[0009] Incidentally, conventional questionnaires used to investigate the individuality of subjects are in the form of questionnaires that present subjects with answer choices, and in such cases, only predetermined answer results can be obtained. For example, the egogram diagnosis, which diagnoses a person's personality, is known as an example of a questionnaire used to investigate the individuality of subjects.

[0010] For example, in conventional egogram assessments, when multiple questions are presented to the subject, the format is such that answer choices are provided, resulting in results that are limited to discrete responses. However, discrete response results do not necessarily reflect the individuality of the subject and therefore do not provide high-resolution results.

[0011] The disclosed technology was developed in consideration of the above circumstances and provides an information processing device, method, and program that can obtain questionnaire results that reflect the individuality of the subjects by presenting an environment in which subjects can continuously provide free answers without being restricted to answering from a set of options. [Means for solving the problem]

[0012] To achieve the above objective, a first aspect of this disclosure is an information processing device in an information processing system including a user terminal and an information processing device, the information processing device including: a control unit that displays a screen on the display unit of a user terminal on which the user can answer a plurality of questions used in a questionnaire to investigate the individuality of the user using continuous values ​​when presenting the user with a plurality of questions; and an answer acquisition unit that acquires continuous values ​​representing the answers entered by the user operating the user terminal and stores the continuous values ​​representing the answers in a storage unit.

[0013] A second aspect of this disclosure is an information processing method in which a computer performs a process in which, when presenting a user with a series of questions used in a questionnaire to investigate the individuality of the user, a screen is displayed on the display unit of the user terminal on which the user can answer the questions using continuous values, and the continuous values ​​representing the answers entered by the user operating the user terminal are obtained and stored in a storage unit.

[0014] A third aspect of this disclosure is an information processing program for causing a computer to execute a process that, when presenting a user with a series of questions used in a questionnaire to investigate the individuality of the user, displays a screen on the display unit of a user terminal on which the user can answer the questions using continuous values, obtains the continuous values ​​representing the answers entered by the user operating the user terminal, and stores the continuous values ​​representing the answers in a storage unit. [Effects of the Invention]

[0015] Disclosure technology offers the advantage of obtaining questionnaire results that reflect the individual characteristics of the subjects. [Brief explanation of the drawing]

[0016] [Figure 1] This figure shows an example of a schematic configuration of an information processing system according to an embodiment. [Figure 2] This is a diagram illustrating an embodiment. [Figure 3] This is a presentation example of questions related to egogram diagnosis and the like. [Figure 4] This is a diagram showing an example of an aptitude test. [Figure 5] This is a diagram for explaining the normal distribution. [Figure 6] This is a diagram for explaining the first determination algorithm of the embodiment. [Figure 7] This is a diagram for explaining the second determination algorithm of the embodiment. [Figure 8] This is a diagram showing an example of a computer that constitutes a user terminal or a server. [Figure 9] This is a diagram showing an example of information processing executed by the server of the embodiment. [Mode for Carrying Out the Invention]

[0017] Hereinafter, embodiments of the disclosed technology will be described in detail with reference to the drawings.

[0018] <Information Processing Apparatus of Embodiment> FIG. 1 shows an information processing system 10 according to the embodiment. As shown in FIG. 1, the information processing system 10 of the present embodiment includes a plurality of user terminals 12A, 12B, 12C, ..., and a server 14 which is an example of the information processing apparatus. Each device is communicably connected via a network 20 such as the Internet, for example. In the following description, any one of the plurality of user terminals 12A, 12B, 12C, ... is simply referred to as a user terminal 12. In the present embodiment, a case where the questionnaire for investigating the user's individuality is a questionnaire related to egogram diagnosis will be described as an example.

[0019] (User Terminal 12) The user terminal 12 is operated by a user who undergoes egogram diagnosis. As will be described later, the user terminal 12 is implemented by a computer.

[0020] (Server 14) Server 14 performs an egogram diagnosis on the user operating the user terminal 12. As will be described later, Server 14 is implemented by a computer.

[0021] Figure 2 is a diagram illustrating this embodiment. As shown in Figure 2, in this embodiment, a questionnaire regarding egogram diagnosis is administered to a user operating the user terminal 12. Specifically, the server 14 displays several questions regarding egogram diagnosis on the display unit (e.g., touch panel display) of the user terminal 12. The user then answers the questions displayed on the display unit by operating their user terminal 12. In this embodiment, the example of a questionnaire regarding egogram diagnosis is used, but it is not limited to this. This embodiment can be applied to any questionnaire that investigates the individuality of the user.

[0022] In this embodiment, an aptitude test is conducted before conducting a questionnaire related to egogram diagnosis, etc. Specifically, as shown in Figure 2, an aptitude test is conducted when conducting a questionnaire consisting of multiple questions related to egogram diagnosis, etc. If the user passes the aptitude test, the multiple questions related to egogram diagnosis, etc. are displayed on the display unit of the user terminal 12. On the other hand, if the user fails the aptitude test, the questionnaire is canceled.

[0023] In this embodiment, answers to multiple questions related to egogram diagnosis, etc., can be provided using continuous quantities. Figure 3 shows an example of the presentation of questions related to egogram diagnosis, etc., in this embodiment. As shown in Figure 3, the user can answer the degree of applicability to question XX related to egogram diagnosis, etc., using continuous quantities. Conventional egogram diagnosis questions were limited to answers with a choice of 3 to 5 levels of applicability. In contrast, in this embodiment, by obtaining answers to questions related to egogram diagnosis, etc., using continuous quantities, it becomes possible to perform various individualized evaluations, classifications, and diagnoses that are not limited to the given choices. Further details will be described later.

[0024] Figure 4 shows an example of an aptitude test. By conducting tests 1 to 3 as shown in Figure 4, it is possible to determine whether or not a user is suitable for an egogram diagnosis, etc.

[0025] Specifically, for the question in Figure 4, Test 1, "Do you think a 10kg bag is heavier than a 1kg bag?", the correct answer is "Yes," and answers of "No" or somewhere between "Yes" and "No" are incorrect. In this way, aptitude tests include questions where either a positive or negative answer is correct.

[0026] Furthermore, the question in Test 2 of Figure 4, "Do you have any disabilities or problems that prevent you from answering questions using devices such as smartphones, personal computers, or tablets?", is intended for people who have difficulty operating electronic devices (for example, the elderly). Thus, the aptitude test includes questions related to the operation of the user terminal 12.

[0027] Furthermore, in Figure 4, for Test 3, "Please give an answer that is neither completely 'applies' nor completely 'does not apply'," the correct answer is to indicate a degree of relevance between "applies" and "does not apply." Thus, aptitude tests include questions where neither affirmative nor negative is the correct answer, but rather something in between.

[0028] As shown in Figure 3, in this embodiment, based on the answers obtained using continuous quantities, the individuality and state of the user are evaluated, classified, and diagnosed without being limited to the given options, enabling mathematical analysis and generating data that can be applied to machine learning. In this embodiment, the results of the egogram diagnosis obtained at the present time are evaluated based on the distribution representing the results of the user's past egogram diagnoses, etc.

[0029] Figure 5 is a diagram illustrating the normal distribution. As shown in Figure 5, consider the case where the mean of the normal distribution is μ and the standard deviation is σ. In this case, approximately 68% of the data falls within the region from -σ to σ. Approximately 95% of the data falls within the region from -2σ to 2σ. Furthermore, approximately 99.7% of the data falls within the region from -3σ to 3σ. In this embodiment, the above properties of the normal distribution are used to evaluate the results of the egogram diagnosis obtained so far.

[0030] Figure 6 is a diagram illustrating the first judgment algorithm of this embodiment. As shown in Figure 6, consider a case where the egogram diagnosis yields scores for five ego states: CP (Critical Parent), NP (Nurturing Parent), A (Adult), FC (Free Child), and AC (Adapted Child).

[0031] In this case, the first judgment algorithm calculates the mean μ and standard deviation σ for a given user from past data, as shown in Figure 6. Then, as described above, the first judgment algorithm determines, based on which range of the distribution the latest data X obtained at the present time falls into, whether the degree of change in the user's ego state corresponding to the latest data X, which is the result of the egogram diagnosis, is "average," "changed," or "characteristic change."

[0032] Specifically, as shown in Figure 6, the first decision algorithm determines whether the latest data X is "average," "changed," or "characteristic change" based on the latest data X and the mean μ and standard deviation σ of past data.

[0033] "Average": μ-σ≦X≦μ+σ "Change": μ-2σ≦X<μ-σ or μ+σ <X≦μ+2σ "Characteristic change": X<μ-2σ or μ+2σ <X

[0034] As shown in Figure 6, the latest data X = {CP, NP, A, FC, AC}, so the above judgment is performed for each of the five ego states. Figure 6 illustrates specific numerical values ​​for performing the judgment for each of the five ego states. Therefore, the first judgment algorithm statistically processes the values ​​of each ego state and, when comparing the latest data X with past data, determines the current user state by classifying states that occur with a probability of approximately 68% as "average," states that occur with a probability of approximately 32% as "changed," and states that occur with a probability of approximately 5% as "characteristic change."

[0035] Figure 7 is a diagram illustrating the second determination algorithm of this embodiment. In the second determination algorithm, as shown in Figure 7, the mean μ and standard deviation σ are calculated from all data for a given user (including past data and the latest data X). The latest data X is the data from 2025 / 1 / 4 in the figure. Then, the second determination algorithm determines whether the value obtained by standardizing the latest data X (-1.75, 0.63, 0.48, -0.16, -0.58 in the figure) falls within one of the following ranges: "significantly decreased," "decreased more than usual," "decreased," "average," "increased," "increased more than usual," or "significantly increased."

[0036] Specifically, as shown in Figure 7, the first decision algorithm determines whether the latest data X is "significantly decreased," "decreased more than usual," "decreased," "average," "increased," "increased more than usual," or "significantly increased," based on the standardized latest data X and the mean μ and standard deviation σ of past data.

[0037] "Very low": X < -2 "Lower than usual": -2 ≤ X < -1 "Decrease": -1 ≤ X < 0 "Average":0 "Increase": 0 <X≦1 "Increased compared to usual": 1 <X≦2 "Increased significantly": 2 <X

[0038] Therefore, in the second judgment algorithm, if the value obtained by statistically processing the value of each ego state and standardizing the latest data is 0, the change is considered "average". Furthermore, in the second judgment algorithm, if the value obtained by standardization is positive in a state that occurs with a probability of approximately 68%, it is considered an "increase", and if the value is negative, it is considered a "decrease". Furthermore, in the second judgment algorithm, if the value obtained by standardization is positive in a state that occurs with a probability of approximately 32%, it is considered a "greater increase", and if the value is negative, it is considered a "greater decrease". Furthermore, in the second judgment algorithm, if the value obtained by standardization is positive in a state that occurs with a probability of approximately 5%, it is considered a "very great increase", and if the value is negative, it is considered a "very great decrease".

[0039] Furthermore, if, for example, an egogram assessment is conducted once a day or once a week, the user may memorize the order of the questions in the egogram assessment. In such cases, it is possible that an accurate egogram assessment result may not be obtained.

[0040] Therefore, in this embodiment, when conducting multiple egogram diagnoses or similar assessments for the same user at intervals, the questions for the current egogram diagnosis are presented to the user in a different order than the order of the questions presented during the previous egogram diagnosis or similar assessment. Specifically, when presenting multiple questions to the same user, the order of the questions is randomly rearranged each time an egogram diagnosis or similar assessment is conducted. This makes it possible to conduct egogram diagnoses or similar assessments that reduce bias and preconceptions due to the user's memory and reflect the individuality of the user's responses. This will be explained in detail below.

[0041] As shown in Figure 1, the server 14 functionally comprises a control unit 140, a response acquisition unit 142, a data storage unit 144, and an output unit 146.

[0042] When the control unit 140 presents the user with multiple questions used in performing an egogram diagnosis, etc., it displays a screen on the user terminal 12's display unit that allows the user to answer the questions using continuous values. Specifically, the control unit 140 displays a screen on the user terminal 12's display unit as shown in Figure 3.

[0043] The response acquisition unit 142 acquires a sequence of values ​​representing the response entered by the user operating the user terminal 12. The response acquisition unit 142 then stores the sequence of values ​​representing the response in the data storage unit 144.

[0044] The data storage unit 144 stores sequential values ​​representing the answers obtained by the answer acquisition unit 142. The data storage unit 144 also stores answers for each user. Furthermore, the data storage unit 144 stores diagnostic results from past egogram diagnoses, etc.

[0045] As mentioned above, when the control unit 140 presents multiple questions to the same user, it presents the questions in a different order than the order in which the questions were presented to the user during the previous egogram diagnosis, etc. Specifically, the control unit 140 randomly rearranges the order of the questions each time the egogram diagnosis, etc. is performed and presents them to the user.

[0046] Furthermore, as described above, the control unit 140 displays appropriate questions on the display unit of the user terminal 12. These questions are different from the questions used in the egogram diagnosis, and are intended to determine whether the user is in a suitable state to receive the egogram diagnosis. Specifically, the control unit 140 displays a screen on the display unit of the user terminal 12 as shown in Figure 4. The control unit 140 then determines whether the user is in a suitable state to receive the egogram diagnosis based on the user's answers to the appropriate questions. If the user is in a suitable state to receive the egogram diagnosis, the control unit 140 displays the questions used in the egogram diagnosis on the display unit of the user terminal 12.

[0047] Furthermore, as described above, the control unit 140 acquires multiple egogram diagnosis results, etc., from the same user, and generates information representing changes between egogram diagnosis results, etc., based on the multiple egogram diagnosis results, etc. Specifically, the control unit 140 generates information representing changes based on the distribution of past egogram diagnosis results, etc., obtained from the same user, and which range of the distribution the current egogram diagnosis result, etc., obtained from the same user corresponds to. When generating information representing changes, the first judgment algorithm or the second judgment algorithm, etc., described above is used. For this reason, the information representing changes may be, for example, "average," "change," or "characteristic change." Alternatively, the information representing changes may be, for example, "significant decrease," "decreased compared to usual," "decrease," "average," "increase," "increase compared to usual," or "significant increase."

[0048] The output unit 146 outputs information representing the changes acquired by the control unit 140, as well as diagnostic results such as the egogram diagnosis. For example, the information representing the changes and the results of the egogram diagnosis are displayed on the display unit of the user terminal 12.

[0049] The user terminal 12 and server 14 can be implemented, for example, by the computer 50 shown in Figure 8. The computer 50 includes a CPU 51, a memory 52 as a temporary storage area, and a non-volatile storage unit 53. The computer 50 also includes an input / output interface (I / F) 54 to which external devices and output devices (for example, the display unit of the user terminal 12) are connected, and a read / write (R / W) unit 55 that controls the reading and writing of data to the recording medium. The computer 50 also includes a network I / F 56 that connects to a network such as the Internet. The CPU 51, memory 52, storage unit 53, input / output I / F 54, R / W unit 55, and network I / F 56 are connected to each other via a bus 57.

[0050] The storage unit 53 can be implemented using a Hard Disk Drive (HDD), Solid State Drive (SSD), flash memory, etc. The storage unit 53, as a storage medium, stores a program that allows the computer 50 to function. The CPU 51 reads the program from the storage unit 53, loads it into memory 52, and sequentially executes the processes contained in the program.

[0051] [Operation of Server 14 in the Embodiment] Next, the specific operation of the server 14 in this embodiment will be described. The server 14 performs the information processing shown in Figure 9.

[0052] First, in step S100, the control unit 140 causes the appropriate question to be displayed on the display unit of the user terminal 12.

[0053] The user answers the appropriate questions displayed on the display unit of the user terminal 12.

[0054] Next, in step S102, the control unit 140 obtains the user's response to the appropriate question.

[0055] In step S104, the control unit 140 determines whether the answer obtained in step S102 is appropriate. If the answer is appropriate, the process proceeds to step S106. On the other hand, if the answer is not appropriate, the process ends.

[0056] In step S106, the control unit 140 displays the questions for the egogram diagnosis, etc., on the display unit of the user terminal 12. At this time, the control unit 140 presents the questions for the egogram diagnosis, etc., to the user in a different order than the order of the questions in the previous egogram diagnosis, etc.

[0057] The user answers questions such as those related to the egogram diagnosis displayed on the display unit of the user terminal 12.

[0058] In step S108, the response acquisition unit 142 acquires a sequence of values ​​representing the response entered by the user. The response acquisition unit 142 then stores the sequence of values ​​representing the response in the data storage unit 144.

[0059] In step S110, the control unit 140 generates information representing changes in the results of the ego gram diagnosis obtained this time, based on past ego gram diagnosis results obtained from the same user. The information representing changes may, for example, indicate whether the results of the ego gram diagnosis obtained this time fall under "average," "change," or "characteristic change." Alternatively, the information representing changes may, for example, indicate whether the results of the ego gram diagnosis obtained this time fall under "significantly decreased," "decreased compared to usual," "decreased," "average," "increased," "increased compared to usual," or "significantly increased."

[0060] In step S112, the output unit 146 outputs information representing the changes obtained in step S110 and the results of the egogram diagnosis, etc.

[0061] As described above, the server in this embodiment displays a screen on the user terminal's display unit that allows the user to answer questions using continuous values ​​when presenting the user with multiple questions used in an egogram diagnosis, which is an example of a questionnaire used to investigate the user's individuality or generate training data for machine learning. The server acquires the continuous values ​​representing the answers entered by the user operating the user terminal and stores the continuous values ​​representing the answers in a storage unit. This makes it possible to obtain diagnostic results that reflect individuality more accurately when performing egogram diagnoses, etc.

[0062] Furthermore, this embodiment makes it possible to improve the accuracy of egogram diagnoses and the like by digitally displaying the questions. In addition, this embodiment makes it possible to obtain more appropriate egogram diagnoses and the like by presenting questions to the user to determine the respondent's suitability. Specifically, it becomes possible to quantitatively evaluate the degree of suitability of the respondent to questions such as egogram diagnoses, and it can be used in the development of deep analysis using mathematics and learning models using machine learning.

[0063] Furthermore, this embodiment allows for the input of continuous quantities for answers to questions that were previously entered using multiple-choice options. This enables not only the quantitative evaluation of human psychological and personality traits, but also the development of mathematical analysis and machine learning models. As a result, it becomes possible to apply this to human mental health management, the development of indicators for evaluating human psychological and personality traits, the provision of individualized counseling, and individualized diagnosis and treatment. Furthermore, in this embodiment, it is possible to evaluate the results of the egogram diagnosis obtained at the present time based on the distribution representing the results of the user's past egogram diagnoses. This makes it possible to accurately assess the user's current psychological state and to appropriately manage the user's mental health.

[0064] Furthermore, the technology disclosed herein is not limited to the embodiments described above, and various modifications and applications are possible without departing from the spirit of this invention.

[0065] <Example 1> For example, the above embodiment describes a case where the questionnaire for investigating the individuality of the user is a questionnaire related to egogram diagnosis, but it is not limited to this. The above embodiment can be applied to any questionnaire for investigating the individuality of the user. For example, it can be applied to health-related quality of life questionnaires such as WHOQOL-100 / BREF / 26 (a questionnaire developed by the World Health Organization (WHO) to measure an individual's quality of life (QOL)) and SF-36 (36-Item Short-Form Health Survey). It can also be applied to dementia-related questionnaires such as MMSE (Mini-Mental State Examination), MoCA (Montreal Cognitive Assessment Scale), MoCA-J (Japanese version of MoCA), SED-11Q, and DDQ43. Alternatively, it can be applied to questionnaires related to the marketing of products or services, and is not limited to analysis using factor analysis or principal component analysis, but can also be used for deep analysis using mathematical methods.

[0066] <Modification 2> The continuous data representing user responses obtained by the above embodiment can be used as training data in machine learning. In conventional questionnaires that present multiple-choice options, the limited number of options prevents obtaining responses that adequately reflect the individuality and psychological characteristics of users. Furthermore, in conventional questionnaires that present multiple-choice options, the response results are discrete values, making such data difficult to use as training data for machine learning. Moreover, the performance of learning models obtained from deep learning and reinforcement learning using machine learning is limited, making it difficult to develop learning models that can extract or generate results and features that are difficult to derive by humans or mathematical analysis. In contrast, the above embodiment allows obtaining continuous response results that reflect the individuality of users, and such data can be used as training data in deep learning and reinforcement learning using machine learning. In particular, information that directly represents a person's psychological state does not exist on the internet. Therefore, even if a machine learning model or deep learning model is trained using information that exists on the internet, it is not possible to generate a machine learning model or deep learning model that appropriately reflects a person's psychological state. In order to generate a high-quality machine learning model or deep learning model, it is necessary to prepare high-quality training data. In contrast, according to this embodiment, it is possible to obtain continuous values ​​that reflect the individuality of the user as a response to a questionnaire, and such data can be used as high-quality training data. For this reason, the control unit of the information processing device in this embodiment may generate training data that includes multiple continuous values, and is intended for generating a machine learning model or a deep learning model, based on multiple continuous values ​​obtained when the user is given multiple questionnaires. Furthermore, the control unit of the information processing device may generate a trained model that reflects the individuality of the user by training a machine learning model or a deep learning model based on the training data.

[0067] Furthermore, although the present specification describes an embodiment in which the program is pre-installed, it is also possible to provide the program by storing it on a computer-readable recording medium.

[0068] In addition, the processing that the CPU reads and executes in the above embodiment may be executed by various processors other than the CPU. Examples of such processors include PLDs (Programmable Logic Devices) such as FPGAs (Field-Programmable Gate Arrays) whose circuit configuration can be changed after manufacturing, and dedicated electrical circuits that are processors with circuit configurations specifically designed to execute specific processing, such as ASICs (Application Specific Integrated Circuits). Alternatively, a GPGPU (General-purpose graphics processing unit) may be used as the processor. Furthermore, each processing may be executed by one of these various processors, or by a combination of two or more processors of the same or different types (for example, multiple FPGAs, and a combination of a CPU and an FPGA). More specifically, the hardware structure of these various processors is an electrical circuit that combines circuit elements such as semiconductor elements.

[0069] Furthermore, while the above embodiments describe a configuration in which the program is pre-stored (installed) on storage, the invention is not limited to this. The program may be provided in a form stored on a non-transitory storage medium such as a CD-ROM (Compact Disk Read Only Memory), DVD-ROM (Digital Versatile Disk Read Only Memory), or USB (Universal Serial Bus) memory. Alternatively, the program may be downloaded from an external device via a network.

[0070] Furthermore, each process in this embodiment may be configured by a computer or server equipped with a general-purpose processing unit and storage device, and each process may be executed by a program. This program is stored in the storage device and can be recorded on a recording medium such as a magnetic disk, optical disk, or semiconductor memory, or provided over a network. Of course, none of the other components have to be implemented by a single computer or server; they may be implemented in a distributed manner across multiple computers connected by a network.

[0071] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0072] (Note) The following is an addendum regarding the nature of this disclosure.

[0073] (Note 1) An information processing device in an information processing system including a user terminal and an information processing device, When presenting users with multiple questions used in a survey to investigate their individual characteristics, A control unit that displays a screen on the user terminal's display unit that allows the user to answer the aforementioned question using continuous values, A response acquisition unit acquires a sequence of values ​​representing the response entered by the user operating the user terminal, and stores the sequence of values ​​representing the response in a storage unit. Information processing device including (Note 2) When presenting multiple questions to the same user, The control unit presents the user with multiple questions in a different order than the order in which the user was presented with the multiple questions during the previous survey. The information processing apparatus according to claim 1. (Note 3) When presenting multiple questions to the same user, The control unit randomly rearranges the order of multiple questions each time a survey is conducted and presents them to the user. The information processing apparatus according to claim 1 or claim 2. (Note 4) The control unit, An appropriate question, which is different from the questions in the aforementioned survey and is intended to check whether the user is in a suitable condition to take the survey, is displayed on the display unit of the user terminal. Based on the user's responses to the aforementioned suitability questions, it is determined whether the user is in a suitable condition to take the survey. When the user is in a suitable state to take the survey, the questions of the survey are displayed on the display unit of the user terminal. The information processing apparatus according to claim 1 or claim 2. (Note 5) The control unit, Obtain the results of multiple surveys obtained from the same user, Based on the results of multiple surveys, information representing the changes between the survey results is generated. Output information representing the aforementioned change. The information processing apparatus according to claim 2 or claim 3. (Note 6) The control unit, Based on a distribution representing past survey results obtained from the same user, information representing the change is generated based on which range of the distribution the current survey results obtained from the same user correspond to. The information processing apparatus according to claim 5. (Note 7) The control unit, Based on the multiple continuous values ​​obtained when conducting multiple surveys with the user, training data comprising the multiple continuous values ​​is generated, and training data for generating a machine learning model or a deep learning model is generated. An information processing device as described in any one of the appendices 1 to 6. (Note 8) The control unit, Based on the aforementioned training data, a machine learning model or a deep learning model is trained to generate a trained model that reflects the individuality of the user. The information processing device described in Appendix 7. (Note 9) When presenting users with multiple questions used in a survey to investigate their individual characteristics, A screen is displayed on the user terminal's display unit that allows the user to answer the aforementioned question using a continuous value. The system acquires a sequence of values ​​representing the answer entered by the user operating the user terminal, and stores the sequence of values ​​representing the answer in a storage unit. An information processing method in which a computer performs the processing. (Note 10) When presenting users with multiple questions used in a survey to investigate their individual characteristics, A screen is displayed on the user terminal's display unit that allows the user to answer the aforementioned question using a continuous value. The system acquires a sequence of values ​​representing the answer entered by the user operating the user terminal, and stores the sequence of values ​​representing the answer in a storage unit. An information processing program that causes a computer to perform a task. [Explanation of Symbols]

[0074] 10 Information Processing Systems 12 User terminals 14 Servers 140 Control Unit 142 Answer acquisition part 144 Data Storage Unit 146 Output section

Claims

1. An information processing device in an information processing system including a user terminal and an information processing device, When presenting users with multiple questions used in a survey to investigate their individual characteristics, A control unit that displays a screen on the user terminal's display unit that allows the user to answer the aforementioned question using continuous values, A response acquisition unit acquires a sequence of values ​​representing the response entered by the user operating the user terminal, and stores the sequence of values ​​representing the response in a storage unit. Information processing device including

2. When presenting multiple questions to the same user, The control unit presents the user with multiple questions in a different order than the order in which the user was presented with the multiple questions during the previous survey. The information processing apparatus according to claim 1.

3. When presenting multiple questions to the same user, The control unit randomly rearranges the order of multiple questions each time a survey is conducted and presents them to the user. The information processing apparatus according to claim 1 or claim 2.

4. The control unit, An appropriate question, which is different from the questions in the aforementioned survey and is intended to check whether the user is in a suitable condition to take the survey, is displayed on the display unit of the user terminal. Based on the user's responses to the aforementioned suitability questions, it is determined whether the user is in a suitable condition to take the survey. When the user is in a suitable state to take the survey, the questions of the survey are displayed on the display unit of the user terminal. The information processing apparatus according to claim 1 or claim 2.

5. The control unit, Obtain the results of multiple surveys obtained from the same user, Based on the results of multiple surveys, information representing the changes between the survey results is generated. Output information representing the aforementioned change. The information processing apparatus according to claim 2 or claim 3.

6. The control unit, Based on a distribution representing past survey results obtained from the same user, information representing the change is generated based on which range of the distribution the current survey results obtained from the same user correspond to. The information processing apparatus according to claim 5.

7. The control unit, Based on the multiple continuous values ​​obtained when conducting multiple surveys with the user, training data comprising the multiple continuous values ​​is generated, and training data for generating a machine learning model or a deep learning model is generated. The information processing apparatus according to claim 1 or claim 2.

8. The control unit, Based on the aforementioned training data, a machine learning model or a deep learning model is trained to generate a trained model that reflects the individuality of the user. The information processing apparatus according to claim 7.

9. When presenting users with multiple questions used in a survey to investigate their individual characteristics, A screen is displayed on the user terminal's display unit that allows the user to answer the aforementioned question using a continuous value. The system acquires a sequence of values ​​representing the answer entered by the user operating the user terminal, and stores the sequence of values ​​representing the answer in a storage unit. An information processing method in which a computer performs the processing.

10. When presenting users with multiple questions used in a survey to investigate their individual characteristics, A screen is displayed on the user terminal's display unit that allows the user to answer the aforementioned question using a continuous value. The system acquires a sequence of values ​​representing the answer entered by the user operating the user terminal, and stores the sequence of values ​​representing the answer in a storage unit. An information processing program that causes a computer to perform a task.

Images