User analysis support apparatus, target selection support apparatus, user analysis support method, target selection support method, user analysis support program, target selection support program, and recording medium

Abstract

To provide a user analysis support apparatus, method and program, and a target selection support apparatus, method and program configured to support analyzing the true intent that a user does not realize.SOLUTION: A user analysis support apparatus 10 includes a user input information acquisition unit, an examination unit, a question presentation unit, an answer acquisition unit, an analysis unit, and an output unit. The user input information acquisition unit acquires user input information including a subject to be examined. The examination unit generates input examination information obtained by examining the user input information. The question presentation unit presents a question based on the input analysis information. The answer acquisition unit acquires an answer to the question from a user. The examination unit generates an answer examination information obtained by examining the answer. The analysis unit generates analysis information obtained by analyzing the subject included in the user input information based on at least one of the input examination information and the answer examination information. The output unit outputs the analysis information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a user analysis support device, a target selection support device, a user analysis support method, a target selection support method, a user analysis support program, a target selection support program, and a recording medium. [Background technology]

[0002] In recent years, in new business planning and the like, a team consisting of several members may be formed to conduct a workshop. In conducting a workshop, it is necessary to select appropriate personnel (e.g., a facilitator, etc.) for the team, and a publicly known personnel matching system is used. For example, the personnel matching system of Patent Document 1 has a means for storing job extraction information that specifies a required job type and its required proficiency for each job information, a means for storing job seeker extraction information that specifies a combination of multiple applicable job types and possessed proficiency from a job seeker, a means for comparing the required proficiency of the job extraction information with the possessed proficiency of the job seeker extraction information based on the job type of the stored job seeker information, and a means for simultaneously displaying multiple job information pieces whose possessed proficiency is equal to or higher than the required proficiency as a result of the comparison, and is a job information search system that searches for suitable job information from preregistered job information in response to the request of a job seeker. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2002-157450 A Summary of the Invention [Problem to be solved by the invention]

[0004] In the human resources matching system of Patent Document 1, when registering job information, the employer must specify and input the required job type and required proficiency required for the employer's project. In order for the employer to specify the required job type and required proficiency required for the employer's project, the employer must understand the purpose of the project, particularly its essence. However, the purpose of the project as conceived by the employer does not necessarily match the essence of the project. Moreover, not limited to job recruitment in projects, people's surface thoughts do not necessarily match their true essence.

[0005] Therefore, the present disclosure aims to provide a user analysis support device, a target selection support device, a user analysis support method, a target selection support method, a user analysis support program, a target selection support program, and a recording medium that can support analysis of true intentions that the user himself is not aware of. [Means for solving the problem]

[0006] In order to achieve the above object, the user analysis support device of the present disclosure includes: The system includes a user input information acquisition unit, an analysis unit, a question presentation unit, an answer acquisition unit, an analysis unit, and an output unit, The user input information acquisition unit acquires user input information, the user input information includes a subject to be analyzed; The analysis unit generates input analysis information by analyzing the user input information, The question presenting unit presents a question based on the input analysis information; the answer acquisition unit acquires an answer from the user to the question, The analysis unit generates answer analysis information by analyzing the answers, The analysis unit generates analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information, The output unit outputs the analysis information.

[0007] The target selection support device of the present disclosure is A user analysis unit and a target selection unit are included, The user analysis unit includes the user analysis support device of the present disclosure, The target selection unit selects at least one target appropriate for the user based on the analysis information generated by the user analysis unit and target characteristic information.

[0008] The user analysis support method of the present disclosure includes: The method includes a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step, The user input information acquiring step acquires user input information, the user input information includes a subject to be analyzed; The analyzing step includes generating input analysis information by analyzing the user input information, The question presenting step presents a question based on the input analysis information, The answer acquisition step acquires an answer from the user to the question, The analysis step includes generating answer analysis information by analyzing the answers, The analysis step generates analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information, The output step outputs the analysis information. The method for supporting user analysis is such that each of the steps is executed by a computer.

[0009] The target selection support method of the present disclosure includes: A user analysis step and a target selection step are included; The user analysis step includes the user analysis support method of the present disclosure, The target selection step selects at least one target appropriate for the user based on the analysis information generated by the user analysis unit and target feature information. The object selection support method includes steps executed by a computer.

[0010] The user analysis support program disclosed herein is The method includes a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step. The user input information acquisition step acquires user input information, the user input information includes a subject to be analyzed; The analysis step includes generating input analysis information by analyzing the user input information; the question presenting step presents a question based on the input analysis information; the answer acquisition step acquires an answer from the user to the question; The analysis step includes generating answer analysis information by analyzing the answer, The analysis step includes generating analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information; The output step outputs the analysis information. The program is for causing a computer to execute each of the above procedures.

[0011] The target selection support program disclosed herein is Including a user analysis procedure and a target selection procedure; The user analysis procedure is executed by the user analysis support program of the present disclosure, The target selection step includes selecting at least one target appropriate for the user based on the analysis information generated by the user analysis unit and target feature information. The program is for causing a computer to execute each of the above procedures.

[0012] The recording medium of the present disclosure includes: A computer-readable recording medium having recorded thereon a program for causing a computer to execute each of the above procedures. Effect of the Invention

[0013] According to the present disclosure, it is possible to assist in the analysis of true intentions that the user himself is not aware of. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is a block diagram showing a configuration of an example of a user analysis support device according to the present disclosure. [Diagram 2] FIG. 2 is a block diagram showing an example of a hardware configuration of the user analysis support device of the present disclosure. [Diagram 3] FIG. 3 is a flowchart showing an example of processing in the user analysis support device of the present disclosure. [Figure 4] FIG. 4 is a block diagram showing a configuration of an example of a target selection support device according to the present disclosure. [Diagram 5] FIG. 5 is a block diagram illustrating an example of a hardware configuration of a target selection support device according to the present disclosure. [Figure 6] FIG. 6 is a flowchart showing an example of processing in the target selection support device of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Next, an embodiment of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiment. In each of the following drawings, the same parts are given the same reference numerals. In addition, the description of each embodiment can be mutually incorporated unless otherwise specified, and the configurations of each embodiment can be combined unless otherwise specified.

[0016] [Embodiment 1] The user analysis support device of the present disclosure will be described with reference to Fig. 1. Fig. 1 is a block diagram showing a configuration of an example of a user analysis support device 10 of the present disclosure. As shown in Fig. 1, the user analysis support device 10 (hereinafter also referred to as "the device 10") includes a user input information acquisition unit 11, an analysis unit 12, a question presentation unit 13, an answer acquisition unit 14, an analysis unit 15, and an output unit 16. Although not shown, the device 10 may also include, for example, a memory unit.

[0017] The device 10 may be, for example, a single device including each of the above-mentioned units, or a device to which each of the above-mentioned units can be connected via a communication line network. The device 10 may be connected to an external device described later via a communication line network. The communication line network is not particularly limited, and a known network may be used, for example, wired or wireless. Examples of the communication line network include an Internet line, a World Wide Web (WWW), a telephone line, a Local Area Network (LAN), a Storage Area Network (SAN), a Delay Tolerant Networking (DTN), a Low Power Wide Area (LPWA), and a Local 5G (L5G). Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), a Local 5G, and a LPWA. Examples of the wireless communication may include a form in which each device directly communicates with each other (Ad Hoc communication), an infrastructure (infrastructure communication), and an indirect communication via an access point. The device 10 may be incorporated into a server as a system, for example. The device 10 may be, for example, a personal computer (PC, for example, desktop type or notebook type) on which the program of the present disclosure is installed, a smartphone, a tablet terminal, etc. Furthermore, the device 10 may be in the form of cloud computing or edge computing, for example, in which at least one of the units is on a server and the other units are on a terminal.

[0018] 2 illustrates a block diagram of a hardware configuration of the present device 10. The present device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, a memory 102, a bus 103, a storage device 104, an input device 105, an output device 106, a communication device 107, etc. Each part of the present device 10 is connected to each other via the bus 103 by each interface (I / F).

[0019] The central processing unit 101 cooperates with other components through a controller (such as a system controller or an I / O controller) and controls the entire device 10. In the device 10, the central processing unit 101 executes, for example, the program disclosed herein and other programs, and also reads and writes various information. Specifically, for example, the central processing unit 101 functions as a user input information acquisition unit 11, an analysis unit 12, a question presentation unit 13, an answer acquisition unit 14, an analysis unit 15, and an output unit 16 in the user analysis support device 10 (hereinafter also referred to as "the device 10"). The device 10 may include other calculation units such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these as a calculation unit.

[0020] The bus 103 can also be connected to, for example, an external device. Examples of the external device include an external storage device (external database, etc.), a printer, an external input device, an external display device, an audio output device such as a speaker, an external imaging device such as a camera, and various sensors such as an acceleration sensor, a geomagnetic sensor, and a direction sensor. The device 10 can be connected to an external network (the communication line network) by, for example, a communication device 107 connected to the bus 103, and can also be connected to other devices such as a user's terminal via the external network.

[0021] An example of the memory 102 is a main memory (primary storage device). When the central processing unit 101 performs processing, the memory 102 reads various operation programs, such as the program of the present disclosure, stored in the storage device 104 described below, and the central processing unit 101 receives data from the memory 102 and executes the program. The main memory is, for example, a RAM (random access memory). The memory 102 may also be, for example, a ROM (read only memory).

[0022] The storage device 104 is also called an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 104 stores an operating program including the program of the present disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive that reads and writes from and to the recording medium. The recording medium is not particularly limited, and may be, for example, an internal or external type, such as a HD (hard disk), a CD-ROM, a CD-R, a CD-RW, an MO, a DVD, a flash memory, or a memory card. The storage device 104 may be, for example, a hard disk drive (HDD) in which a recording medium and a drive are integrated, and a solid state drive (SSD). When the device 10 includes the storage unit, for example, the storage device 104 functions as the storage unit. The storage unit can store, for example, at least one selected from the group consisting of user input information, questions, answers, analytical information, analytical categories, and keywords. The storage unit may function, for example, as an analytical database, which will be described later.

[0023] In the present device 10, the memory 102 and the storage device 104 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 10, and information used when the present device 10 executes processing. In this case, the memory 102 and the storage device 104 may store, for example, the above-mentioned information on the user of the present device. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 102 and the storage device 104, or may be distributed and stored in multiple terminals using block chain technology or the like.

[0024] The device 10 further includes, for example, an input device 105 and an output device 106. The input device 105 may be, for example, a pointing device such as a touch panel, a track pad, or a mouse; a keyboard; an imaging means such as a camera or a scanner; a card reader such as an IC card reader or a magnetic card reader; or an audio input means such as a microphone. The output device 106 may be, for example, a display device such as an LED display or a liquid crystal display; an audio output device such as a speaker; a printer; or the like. In this embodiment, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may be configured as an integrated device, such as a touch panel display.

[0025] Next, an example of the user analysis support method of the present disclosure will be described based on the flowchart of Fig. 3. The user analysis support method of the present disclosure can be implemented as follows, for example, using the user analysis support device 10 shown in Fig. 1 or Fig. 2. Note that the user analysis support method of the present disclosure is not limited to use of the user analysis support device 10 of Fig. 1 or Fig. 2. Fig. 3 is a flowchart showing an example of processing by the user analysis support device 10.

[0026] First, prior to the use of the user analysis support device 10, for example, an analytical database is prepared. The analytical database is, for example, a database in which an analytical category and at least one candidate keyword belonging to the analytical category are linked. The analytical category included in the analytical database may be, for example, one, or two or more. The analytical category and the candidate keyword belonging to the analytical category are not particularly limited, and any category and keyword can be set according to the purpose of use of the device 10. As a specific example, for example, when the device 10 is used to dig into the essence of the goal of a project of a group to which a user belongs, the analytical category may be, for example, a social issue, a problem-solving method, a project target, etc. The candidate keyword linked to the analytical category may be, for example, one, or two or more. The analytical database may further be linked to, for example, a vector of the candidate keyword. The vector of the candidate keyword can be determined by vectorizing each of the candidate keywords using Word2vec or the like.

[0027] The user input information acquisition unit 11 acquires user input information (S1, user input information acquisition step). The user input information is, for example, information input by a user. The user input information includes, for example, a subject to be analyzed. The user may be, for example, one person, or may be two or more. The subject is not particularly limited, and may be, for example, information about the user himself, a project goal in the business to which the user belongs, a workshop goal, etc. The format of the user input information may be, for example, text information or voice information. When the user input information includes text information, for example, input by the input device 105 (for example, a touch panel, a keyboard, etc.) of the device 10 can be acquired. In this case, the device 10 may display, for example, a chat screen and wait for the user to input user input information. Then, the user input information acquisition unit 11 can acquire, for example, information input to the chat screen waiting for input as the user input information. When the user input information includes voice information, for example, voice by the user can be acquired by the input device 105 (for example, a microphone) of the device 10. In this case, the device 10 may, for example, control the microphone to an input standby state and wait for the user to input user input information. The user input information acquisition unit 12 may then acquire, for example, the user's voice input to the microphone during input standby as the user input information. When the user input information is voice information, it is preferable that the user input information acquisition unit 11 converts the acquired voice information into text information, for example. The user input information acquisition unit 12 may, for example, store the user input information in the memory 102 or the storage device 104.

[0028] Next, the analysis unit 12 generates input analysis information by analyzing the user input information (S2, analysis step). For example, the analysis unit 12 analyzes the user input information to extract at least one keyword contained in the user input information. For example, the analysis unit 12 can analyze the text of the user input information by natural language processing such as morphological analysis and extract the keyword contained in the user input information. Next, the analysis unit 12, for example, estimates which of at least one predetermined analysis category the keyword belongs to. For example, the analysis unit 12 can search the analysis database using the extracted keyword as a query and extract an analysis category to which the candidate keyword that matches or is similar to the keyword is linked. Then, the analysis unit 12 can estimate that the keyword belongs to the extracted analysis category and generate a pair of the keyword and the analysis category as the input analysis information. The processing by the analysis unit 12 is not limited to this, and may, for example, perform vectorization processing on the keyword using Word2vec or the like, and extract candidate keywords from the analysis database based on the vector of the keyword. In this case, the analysis unit 12 may, for example, extract candidate keywords in the analysis database that are linked to vectors that have a predetermined degree of similarity with the vector of the keyword. Then, it may be estimated that the keyword belongs to the analysis category linked to the extracted keyword. In addition, when there are multiple estimated keywords, the accuracy of the keyword with respect to the analysis category may be estimated based on the similarity of the vectors, for example. Then, the analysis unit 12 generates, for example, a pair of the keyword and the analysis category as the input analysis information.

[0029] Next, the question presenting unit 13 presents a question based on the input analysis information (S2, question presenting step). For example, based on the input analysis information, the question presenting unit 13 determines whether an analysis condition is satisfied for each of the at least one analysis category, and presents a question related to the analysis category that does not satisfy the analysis condition and the user input information. The analysis condition is not particularly limited, and for example, a condition such as whether the number of keywords estimated to belong to a preset analysis category exceeds a threshold value, whether the integrated value of the accuracy of the keywords estimated to belong to the analysis category exceeds a threshold value, etc. can be set. For example, the question presenting unit 13 can present a question related to the analysis category that does not satisfy the analysis condition for a subject included in the user input information. The question presenting unit 13 may present a question by text (starting a chat) or by audio output, for example.

[0030] The question presenting unit 13 may present a question generated by the device 10, for example, or may present a question generated outside the device 10. When the device 10 generates a question, the question presenting unit 13 can generate the question by using, for example, a known chatbot technology. When the question presenting unit 13 presents a question generated outside the device 10, the question presenting unit 13 can, for example, transmit the user input information and the input analysis information to the outside of the device 10, and generate a question based on the user input information and the input analysis information outside the device 10. The question generated outside the device 10 may be generated by, for example, using a known text analysis process and a chatbot technology, or a person who confirms the user input information and the input analysis information may generate the question. In this case, the question presenting unit 13 can present the question by, for example, acquiring a question generated outside the device.

[0031] The chatbot is not particularly limited, and may be, for example, a scenario-type (rule-based) chatbot or an AI-type chatbot. The scenario-type chatbot can generate questions using, for example, a script used in a conventionally known chatbot. The script is, for example, information that defines the conversation flow (scenario) of the chatbot. The script may be, for example, stored in the memory 102 or storage device 104 of the device 10, or may be stored in an external database. The script defines, for example, a question that combines the keyword and the analysis category. In this case, the chatbot can determine the script based on, for example, the keyword and the analysis category of the user input information, and determine a question to be output to the user based on the script.

[0032] The AI ​​chatbot may be, for example, a machine learning chatbot, a deep learning chatbot, or a chatbot constructed using a large language model (LLM). Examples of chatbots constructed using the large language model include ChatGPT by Open AI, Bing by Microsoft, Bard by Google (Alphabet Inc.), and LLM by NEC Corporation. In this case, the question presenting unit 13 can, for example, input the user input information and the input analysis information to the AI ​​chatbot and cause it to create the question. Specifically, the question presenting unit 13 can generate the question by, for example, giving the AI ​​chatbot a prompt with a constraint imposed thereon, using the user input information and the input analysis information as keywords, so as to generate a question that delves deeper into a subject included in the user input information.

[0033] Next, the answer acquisition unit 14 acquires the user's answer to the question (S4, answer acquisition step). The process by the answer acquisition unit 14 can be performed, for example, in the same manner as the above-mentioned user input information acquisition unit 11. Furthermore, when there are multiple users and the device 10 is executed in a chat format, for example, a reply to the question presented in S3 may be acquired as the user's answer.

[0034] The analysis unit 12 generates answer analysis information by analyzing the answer (S5, analysis step). The analysis unit 12, for example, analyzes the answer to extract at least one keyword contained in the answer, estimates which of the analysis categories the keyword belongs to, and generates a pair of the keyword and the analysis category as the answer analysis information. The process of S5 can be performed in the same manner as S2, except that the answer is used instead of the user input information.

[0035] Furthermore, the device 10 may repeatedly execute the processes from S3 to S5 until a predetermined condition is satisfied. In the repeated process, the question presenter 13 may, for example, present a question based on the answer analysis information instead of or in addition to the input analysis information. The predetermined condition is not particularly limited, and may, for example, be a condition on the amount of information of the keyword estimated to belong to the analysis category. In this case, the device 10 may, for example, determine whether or not the amount of information exceeds a threshold for each analysis category, and if the amount of information for each analysis category does not exceed the threshold, repeatedly execute the processes from S3 to S5, and if the amount of information for each analysis category exceeds the threshold, execute the process of S6.

[0036] The analysis unit 15 generates analysis information by analyzing the subject included in the user input information based on at least one of the input analysis information and the answer analysis information (S6, analysis step). For example, the analysis unit 15 can determine characteristic words for each analysis category from the keywords estimated to belong to the analysis category based on at least one of the input analysis information and the answer analysis information, and generate pairs of the analysis category and the characteristic words as analysis information of the subject. For example, the analysis unit 15 can estimate the relevance of a group of keywords estimated to belong to the same analysis category, and determine the characteristic words based on the relevance. The relevance can be, for example, the centrality of the keyword. In this case, the analysis unit 15 can calculate, for example, degree centrality for a group of keywords estimated to belong to the same analysis category, and determine a keyword with high centrality as a characteristic word of the analysis category. For example, the analysis unit 15 can determine characteristic words for each analysis category using an AI chatbot constructed using the large language model (LLM). In this case, the analysis unit 15 can generate the characteristic words by, for example, inputting the keywords for each analysis category to the AI ​​chatbot and providing a prompt with a constraint condition so as to generate characteristic words highly related to each keyword. The analysis unit 15 may also extract unique words from the input analysis information and the answer analysis information, and select the extracted unique words as the characteristic words. The unique words are, for example, words that are characteristic of a specific field. In this case, the analysis unit 15 can extract the unique words by, for example, referring to a general word dictionary. The general word dictionary is, for example, a database that collects publicly known text information and records the occurrence frequency of words in the collected text information for each word. The analysis unit 15 can extract, as the unique words, words included in the input analysis information and the answer analysis information whose occurrence frequency recorded in the general word dictionary is equal to or less than a predetermined threshold.

[0037] Furthermore, the analysis unit 15 may generate analysis information in which the features of the subject are mapped based on at least one of the input analysis information and the answer analysis information. In this case, the analysis unit 15 can generate analysis information in which the features of each analysis category are mapped by, for example, generating a co-occurrence network of keywords estimated to belong to the same analysis category for each analysis category. Specifically, the analysis unit 15 can generate the co-occurrence network by, for example, mapping the occurrence probability and relevance of word groups included in the input analysis information and the answer analysis information. In this case, the analysis unit 15 may generate a network in which each word group for each analysis category is mapped.

[0038] Then, the output unit 16 outputs the analysis information (S7, output step). The output unit 16 may output the analysis information to, for example, an output device (for example, a display) 106 of the present device 10, or may output the analysis information to the outside of the present device 10 via a communication device 107 connected to the bus 103.

[0039] The device 10 may record the analysis information, for example. In this case, the analysis information and user identification information may be linked and recorded. The user identification information may be any information capable of identifying a user, and may be, for example, information for identifying the user himself or a user terminal owned by the user. Examples of the user identification information include a name, a nickname, an address, a telephone number, an email address, an ID, a password, an IP address, a MAC address, and device-specific information of a terminal (an identification number such as a terminal serial number or an International Mobile Equipment Identifier). The user identification information may be linked to, for example, attribute information of a user. The attribute information is not particularly limited, and may be, for example, information such as a user's gender, age, organization, address, contact information, hobbies, and preferences. The attribute information may be, for example, tag information including a plurality of pieces of information.

[0040] The user analysis support device of the present disclosure can acquire user input information including a subject to be analyzed by a user input information acquisition unit, generate input analysis information by analyzing the user input information by an analysis unit, present a question based on the input analysis information by a question presentation unit, acquire a user's answer to the question by an answer acquisition unit, generate answer analysis information by analyzing the answer by the analysis unit, generate analysis information by analyzing the subject included in the user input information based on at least one of the input analysis information and the answer analysis information by the analysis unit, and output the analysis information by an output unit. Thus, the user analysis support device of the present disclosure can analyze the true meaning of a subject that the user himself is not aware of, for example.

[0041] [Embodiment 2] The second embodiment is a usage example of the user analysis support device of the present disclosure. In the following usage example, a case will be described in which a user is a leader of a new business planning project, inputs the purpose of the project as a subject of analysis, and analyzes the purpose of the project, but the present disclosure is not limited to the following example.

[0042] First, the user inputs the text "The goal to be achieved is to solve the food problem, which is a local issue for children of dual-income families, by focusing on the food waste problem and reuse after the expiration date from the perspective of SDGs, and to increase social value" as the subject of the analysis target to the user analysis support device. The user analysis support device performs morphological analysis on the input text and extracts the keywords "realize", "want to", "goal", "is", "SDGs", "of", "perspective", "from", "food waste", "problem", "best before date", "after", "of", "reuse", "etc", "focus on", "do", "dual-income", "family", "of", "child", "of", "local issue", "is", "food", "problem", "to", "solve", "to", "social value", "to", "increase". Then, the user analysis support device estimates which of the analysis categories (A: problem awareness, B: type (personality), C: target) each keyword contained in the text belongs to. Table 1 below shows keywords inferred to belong to category A, Table 2 below shows keywords inferred to belong to category B, and Table 3 below shows keywords inferred to belong to category C.

[0043] [Table 1]

[0044] [Table 2]

[0045] [Table 3]

[0046] Then, for "Analysis Category C: Target", the number of relevant keywords does not reach the specified number (four words), so the user analysis support device generates a question related to the input subject and analysis category C: target, "What kind of change will the current food problem bring to children's growth?" and presents it to the user. In response to this, it is assumed that the user answers, "I think that there is a risk of early development of modern diseases due to nutritional imbalance." The user analysis support device analyzes the answer and extracts "nutrition" "of" "imbalance" "etc." "from" "development" "to" "delay" "is" "out" "or" "early" "risk" "of" "modern diseases" "of" "is" "there" "is". Then, the user analysis support device estimates which of the analysis categories (A: problem awareness, B: type (personality), C: target) each keyword contained in the answer belongs to. The following Table 4 shows keywords estimated to belong to category A, the following Table 5 shows keywords estimated to belong to category B, and the following Table 6 shows keywords estimated to belong to category C.

[0047] [Table 4]

[0048] [Table 5]

[0049] [Table 6]

[0050] Next, the user analysis support device determines "food waste" as a characteristic word from each keyword ("food," "food waste," "best before date," "recycling") estimated to belong to category A. Similarly, the user analysis support device determines "problem-solving type" as a characteristic word highly related to each keyword ("realization," "goal," "SDGs," "perspective," "problem," "focus," "on-site issue," "social value," "risk") estimated to belong to category B. Similarly, the user analysis support device determines "food education" as a characteristic word from each keyword ("dual-income household," "family," "children," "nutrition," "modern disease," "development") estimated to belong to category C. Then, the user analysis support device generates and outputs a set of "problem awareness: food waste," "type (personality): problem-solving type," and "target: food education" as analysis information (profile) of the subject input by the user: "The goal I want to achieve is to focus on food waste issues and reuse after the best before date from the perspective of SDGs, solve the food problem that is an on-site issue for children in dual-income households, and increase social value."

[0051] As described above, the user analysis support device can make the user aware of other aspects of the subject that the user himself / herself is not aware of by presenting questions to dig deeper into the subject entered by the user. In addition, the user analysis device can generate and output analytical information (profile) that analyzes the subject based on the user's input and answers to the questions.

[0052] [Embodiment 3] The target selection support device of the present disclosure will be described with reference to Fig. 4. Fig. 4 is a block diagram showing a configuration of an example of a target selection support device 20 of the present disclosure. As shown in Fig. 4, the target selection support device 20 (hereinafter also referred to as "the device 20") includes a user analysis unit 10 and a target selection unit 21. Although not shown, the device 20 may include, for example, a storage unit.

[0053] The device 20 may be, for example, a single device including each of the above-mentioned units, or a device to which each of the above-mentioned units can be connected via a communication line network. The device 20 may be connected to an external device described later via a communication line network. The communication line network is not particularly limited, and a known network may be used, for example, wired or wireless. Examples of the communication line network include an Internet line, a World Wide Web (WWW), a telephone line, a Local Area Network (LAN), a Storage Area Network (SAN), a Delay Tolerant Networking (DTN), a Low Power Wide Area (LPWA), and a Local 5G (L5G). Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), a Local 5G, and a LPWA. Examples of the wireless communication may include a form in which each device directly communicates with each other (Ad Hoc communication), an infrastructure (infrastructure communication), and an indirect communication via an access point. The device 20 may be incorporated into a server as a system, for example. The device 20 may be, for example, a personal computer (PC, for example, desktop type or notebook type) in which the program of the present disclosure is installed, a smartphone, a tablet terminal, etc. Furthermore, the device 20 may be in the form of cloud computing or edge computing, for example, in which at least one of the units is on a server and the other units are on a terminal.

[0054] 5 illustrates a block diagram of a hardware configuration of the present device 20. The present device 20 includes, for example, a central processing unit (CPU, GPU, etc.) 201, a memory 202, a bus 203, a storage device 204, an input device 205, an output device 206, a communication device 207, etc. Each part of the present device 20 is connected to each other via the bus 203 by each interface (I / F).

[0055] The central processing unit 201 cooperates with other components through a controller (such as a system controller or an I / O controller) and controls the entire device 20. In the device 20, the central processing unit 201 executes, for example, the program disclosed herein and other programs, and also reads and writes various information. Specifically, for example, the central processing unit 201 functions as a user analysis unit 10 and a target selection unit 21 in the target selection support device 20 (hereinafter also referred to as "the device 20"). The device 20 may include other calculation devices such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these as a calculation device.

[0056] The bus 203 can also be connected to, for example, an external device. Examples of the external device include an external storage device (external database, etc.), a printer, an external input device, an external display device, an audio output device such as a speaker, an external imaging device such as a camera, and various sensors such as an acceleration sensor, a geomagnetic sensor, and a direction sensor. The present device 20 can be connected to an external network (the communication line network) by, for example, a communication device 207 connected to the bus 203, and can also be connected to other devices such as a user's terminal via the external network.

[0057] The memory 202 may be, for example, a main memory (primary storage device). When the central processing unit 201 performs processing, the memory 202 reads various operation programs, such as the program of the present disclosure, stored in the storage device 204 described below, and the central processing unit 201 receives data from the memory 202 and executes the program. The main memory may be, for example, a RAM (random access memory). The memory 202 may also be, for example, a ROM (read only memory).

[0058] The storage device 204 is also called an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 204 stores an operating program including the program of the present disclosure. The storage device 204 may be, for example, a combination of a recording medium and a drive for reading and writing from and to the recording medium. The recording medium is not particularly limited, and may be, for example, an internal or external type, such as a HD (hard disk), a CD-ROM, a CD-R, a CD-RW, an MO, a DVD, a flash memory, a memory card, and the like. The storage device 204 may be, for example, a hard disk drive (HDD) in which a recording medium and a drive are integrated, and a solid state drive (SSD). When the device 20 includes the storage unit, for example, the storage device 204 functions as the storage unit. The storage unit can store, for example, at least one selected from the group consisting of user input information, questions, answers, analysis information, analysis categories, keywords, and target feature information. The storage unit may function, for example, as the above-mentioned analysis database or the below-mentioned selection database.

[0059] In the present device 20, the memory 202 and the storage device 204 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 20, and information used when the present device 20 executes processing. In this case, the memory 202 and the storage device 204 may store, for example, the above-mentioned information on the user of the present device. Note that at least a part of the information may be stored, for example, in an external server other than the memory 202 and the storage device 204, or may be distributed and stored in multiple terminals using block chain technology or the like.

[0060] The device 20 further includes, for example, an input device 205 and an output device 206. The input device 205 may be, for example, a pointing device such as a touch panel, a track pad, or a mouse; a keyboard; an imaging means such as a camera or a scanner; a card reader such as an IC card reader or a magnetic card reader; or an audio input means such as a microphone. The output device 206 may be, for example, a display device such as an LED display or a liquid crystal display; an audio output device such as a speaker; a printer; or the like. In this embodiment, the input device 205 and the output device 206 are configured separately, but the input device 205 and the output device 206 may be configured as an integrated device, such as a touch panel display.

[0061] Next, an example of the target selection support method of the present disclosure will be described with reference to the flowchart of Fig. 6. The target selection support method of the present disclosure can be implemented as follows, for example, using the target selection support device 20 shown in Fig. 4 or Fig. 5. Note that the target selection support method of the present disclosure is not limited to use of the target selection support device 20 of Fig. 4 or Fig. 5. Fig. 6 is a flowchart showing an example of processing by the target selection support device 20.

[0062] The processing by the user analysis unit 10 can be performed in the same manner as S1 to S7 in the first embodiment, and the description thereof can be cited.

[0063] The target selection unit 21 selects at least one target appropriate for the user based on, for example, the analysis information generated by the user analysis unit 10 and the target characteristic information (S21, target selection step). The target is not particularly limited and may be a person, an object, or a facility. The target characteristic information is, for example, information that represents the characteristics of the target, and is stored in association with the identification information of the target. The identification information of the target is not particularly limited as long as it is information that can identify the target, and examples of the identification information include the name, name, nickname, address, telephone number, email address, ID, password, IP address, MAC address, device specific information of the terminal (serial number of the terminal, identification number such as International Mobile Equipment Identifier, etc.). In addition, it is preferable that the target characteristic information is, for example, associated with the analysis category. In addition, the target characteristic information may further include, for example, a compatibility score with other words. Examples of the other words include each candidate keyword recorded in the analysis database. The target feature information may be stored in, for example, the memory 202 or the storage device 204 of the device 20, or may be stored in a selection database outside the device 20. The target feature information may be set to any information, for example, manually set information, or set by the device 20. In the latter case, the analysis of the target feature information may be performed in the same manner as S1 to S7 of the first embodiment. The target selection unit 21 may, for example, compare the characteristic words included in the analysis information with the target feature information, and select a target in which the same target feature information as the characteristic words is recorded, or may select a target in which target feature information in which the compatibility score with the characteristic words is equal to or greater than a predetermined value is recorded. The target selection unit 12 may select, for example, one target, or two or more targets. In the latter case, for example, a target suitable for the user may be selected from a plurality of targets in a ranking format.

[0064] The device 20 may output the selected target, for example. The device 20 may output the selected target to an output device (for example, a display) 206 of the device 20, or may output the target to the outside of the device 20 via a communication device 207 connected to the bus 203.

[0065] In addition, the device 20 may record the selected target, for example. In this case, the selected target and user identification information may be linked and recorded. The user identification information is as described above.

[0066] The target selection support device of the present disclosure can select at least one target appropriate for the user based on the analysis information generated by the user analysis unit and the target feature information. Therefore, the target selection support device of the present disclosure can select an appropriate target based on the true meaning of the subject that the user himself is not aware of, for example. Therefore, for example, when holding a workshop, it is possible to analyze the essence of the subject project by the target selection support device of the present disclosure, and select a facilitator, equipment, etc. that matches the project based on the analysis information.

[0067] [Embodiment 4] The fourth embodiment is an example of use of the target selection support device of the present disclosure. In the following example, a case will be described in which a user is a leader of a new business planning project, inputs the purpose of the project as a subject of analysis, and selects a facilitator suitable for the purpose of the project, but the present disclosure is not limited to the following example.

[0068] First, the user inputs the text "The goal to be achieved is to solve the food problem, which is a local issue for children of dual-income families, by focusing on the food waste problem and reuse after the expiration date from the perspective of the SDGs, and to increase social value" as the subject of the analysis target to the target selection support device. The target selection support device performs morphological analysis on the input text and extracts the keywords "realize", "want to", "goal", "is", "SDGs", "of", "perspective", "from", "food waste", "problem", "best before date", "after", "of", "reuse", "etc", "focus on", "do", "dual-income", "family", "of", "child", "of", "local issue", "is", "food", "problem", "to", "solve", "to", "social value", "to", "increase". Then, the target selection support device estimates which of the analysis categories (A: problem awareness, B: type (personality), C: target) each keyword contained in the text belongs to. Table 1 below shows keywords inferred to belong to category A, Table 2 below shows keywords inferred to belong to category B, and Table 3 below shows keywords inferred to belong to category C.

[0069] [Table 1]

[0070] [Table 2]

[0071] [Table 3]

[0072] Then, since the number of relevant keywords for "Analysis Category C: Target" does not reach the specified number (4 words), the object selection support device generates a question related to the input subject and analysis category C: target, "What changes will the current food problem bring to children's growth?" and presents it to the user. In response to this, it is assumed that the user answers "I think that there is a risk of early development of modern diseases due to nutritional imbalance." The object selection support device analyzes the answer and extracts "nutrition" "of" "imbalance" "etc." "from" "development" "to" "delay" "is" "out" "or" "early" "risk" "of" "modern diseases" "of" "is" "there" "is". Then, the object selection support device estimates which of the analysis categories (A: problem awareness, B: type (personality), C: target) each keyword contained in the answer belongs to. The following Table 4 shows keywords estimated to belong to category A, the following Table 5 shows keywords estimated to belong to category B, and the following Table 6 shows keywords estimated to belong to category C.

[0073] [Table 4]

[0074] [Table 5]

[0075] [Table 6]

[0076] Next, the target selection support device determines "food waste" as a characteristic word from each keyword ("food," "food waste," "best before date," "recycling") estimated to belong to category A. Similarly, the target selection support device determines "problem-solving type" as a characteristic word from each keyword ("realization," "goal," "SDGs," "perspective," "problem," "focus," "on-site issue," "social value," "risk") estimated to belong to category B. Similarly, the target selection support device determines "food education" as a characteristic word from each keyword ("dual-income household," "family," "children," "nutrition," "modern disease," "growth") estimated to belong to category C. Then, the target selection support device generates and outputs a set of "problem awareness: food waste," "type (personality): problem-solving type," and "target: food education" as analysis information (profile) of the subject input by the user: "The goal to be achieved is to focus on food waste issues and reuse after the best before date from the perspective of SDGs, solve the food problem that is an on-site issue for children in dual-income households, and increase social value."

[0077] The target selection support device, for example, refers to a selection database in which target characteristic information of a plurality of facilitators (targets) is recorded, and selects a facilitator appropriate for the theme of the project input by the user based on the analysis information (the set of "problem awareness: food waste", "type (personality): problem-solving type", and "target: food education"). As a specific example, when facilitator A, whose profile is registered as the set of "problem awareness: food waste", "type (personality): problem-finding type", and "target: child-rearing" and facilitator B, whose profile is registered as the set of "problem awareness: community revitalization", "type (personality): problem-solving type", and "target: lonely death" are recorded in the selection database as target characteristic information, the target selection support device compares the characteristic words of each category (problem awareness, type (personality), target) in the analysis information with the words of each category (problem awareness, type (personality), target) in the target characteristic information. Then, for each word in the target characteristic information, facilitator A who has a word (food waste) recorded that matches the characteristic word can be selected as a facilitator appropriate for the subject of the project.

[0078] As described above, the object selection assistance device can select an object appropriate for a subject input by a user, based on analysis information obtained by analyzing the subject.

[0079] [Embodiment 5] The user analysis support program of the present disclosure is a program for causing a computer to execute each step of the above-mentioned user analysis support method. Specifically, the user analysis support program of the present disclosure is a program for causing a computer to execute a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step.

[0080] The user input information acquisition step acquires user input information, the user input information includes a subject to be analyzed; The analysis step includes generating input analysis information by analyzing the user input information; the question presenting step presents a question based on the input analysis information; the answer acquisition step acquires an answer from the user to the question; The analysis step includes generating answer analysis information by analyzing the answer, The analysis step includes generating analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information; The output step outputs the analysis information.

[0081] Furthermore, the user analysis assistance program of the present disclosure can also be said to be a program that causes a computer to function as a user input information acquisition procedure, an analysis procedure, a question presentation procedure, an answer acquisition procedure, an analysis procedure, and an output procedure.

[0082] The user analysis support program of the present disclosure may be implemented by using the description of the user analysis support device and the user analysis support method of the present disclosure. In each of the steps, for example, the "step" can be read as "processing". In addition, the user analysis support program of the present disclosure may be recorded in a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (for example, SSD (Solid State Drive), USB flash memory, SD / SDHC card, etc.), optical disk (for example, CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), floppy (registered trademark) disk (FD), etc. In addition, the user analysis support program of the present disclosure (for example, also referred to as a programming product or a user analysis support program product) may be, for example, distributed from an external computer. The "distribution" may be, for example, distribution via a communication network or distribution via a device connected by a wire. The user analysis support program of the present disclosure may be installed and executed on the device to which it is distributed, or may be executed without being installed.

[0083] [Embodiment 6] The target selection support program of the present disclosure is a program for causing a computer to execute each step of the target selection support method described above. Specifically, the target selection support program of the present disclosure is a program for causing a computer to execute a user analysis procedure and a target selection procedure.

[0084] The user analysis procedure is executed by the user analysis support program of the present disclosure, The target selection step includes selecting at least one target appropriate for the user based on the analysis information generated by the user analysis unit and target characteristic information.

[0085] Furthermore, the target selection assistance program disclosed herein can also be said to be a program that causes a computer to function as a user analysis procedure and a target selection procedure.

[0086] The target selection support program of the present disclosure can be incorporated with the description of the target selection support device and the target selection support method of the present disclosure. For example, the "procedure" in each of the steps can be read as "processing". The target selection support program of the present disclosure may be recorded in a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (for example, SSD (Solid State Drive), USB flash memory, SD / SDHC card, etc.), optical disk (for example, CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), floppy (registered trademark) disk (FD), etc. The target selection support program of the present disclosure (for example, also referred to as a programming product or a target selection support program product) may be, for example, in a form distributed from an external computer. The "distribution" may be, for example, distribution via a communication network or distribution via a device connected by a wire. The target selection support program of the present disclosure may be installed and executed on the device to which it is distributed, or may be executed without being installed.

[0087] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-mentioned embodiments. Various modifications that can be understood by a person skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be appropriately combined with other embodiments.

[0088] <Additional Notes> Some or all of the above embodiments may be described as follows, but are not limited to the following supplementary notes. (Appendix 1) The system includes a user input information acquisition unit, an analysis unit, a question presentation unit, an answer acquisition unit, an analysis unit, and an output unit, The user input information acquisition unit acquires user input information, the user input information includes a subject to be analyzed; The analysis unit generates input analysis information by analyzing the user input information, The question presenting unit presents a question based on the input analysis information; the answer acquisition unit acquires an answer from the user to the question, The analysis unit generates answer analysis information by analyzing the answers, The analysis unit generates analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information, The output unit outputs the analysis information. (Appendix 2) The analysis unit is Analyzing the user input information to extract at least one keyword contained in the user input information; Inferring to which of at least one predetermined analytical category the keyword belongs; 2. A user analysis support device according to claim 1, which generates a pair of the keyword and the analysis category as the input analysis information. (Appendix 3) The question presentation unit, determining whether an analysis condition is satisfied for each of the at least one analysis category based on the input analysis information; presenting a question related to the analysis category that does not satisfy the analysis condition and the user input information; the answer acquisition unit acquires an answer from the user to the question, The analysis unit is Analyzing the answer to extract at least one keyword contained in the answer; Inferring to which of the analysis categories the keyword belongs; generating a pair of the keyword and the analysis category as the answer analysis information; 3. A user analysis support device as described in appendix 2. (Appendix 4) The user analysis support device described in Appendix 3, wherein the analysis unit determines characteristic words for each analysis category from the keywords estimated to belong to the analysis category based on at least one of the input analysis information and the response analysis information, and generates pairs of the analysis category and the characteristic words as analysis information of the subject. (Appendix 5) A user analysis support device according to any one of appendices 1 to 4, wherein the analysis unit generates analysis information that maps features of the subject based on at least one of the input analysis information and the response analysis information. (Appendix 6) A user analysis unit and a target selection unit are included, The user analysis unit includes a user analysis support device according to any one of Supplementary Notes 1 to 5, The target selection unit selects at least one target appropriate for the user based on the analysis information generated by the user analysis unit and target feature information. (Appendix 7) The method includes a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step, The user input information acquiring step acquires user input information, the user input information includes a subject to be analyzed; The analyzing step includes generating input analysis information by analyzing the user input information, The question presenting step presents a question based on the input analysis information, The answer acquisition step acquires an answer from the user to the question, The analysis step includes generating answer analysis information by analyzing the answers, The analysis step generates analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information, The output step outputs the analysis information. A user analysis support method, wherein each of the steps is executed by a computer. (Appendix 8) The analyzing step includes: Analyzing the user input information to extract at least one keyword contained in the user input information; Inferring to which of at least one predetermined analytical category the keyword belongs; A user analysis support method according to claim 7, further comprising generating a pair of the keyword and the analysis category as the input analysis information. (Appendix 9) The question presenting step includes: determining whether an analysis condition is satisfied for each of the at least one analysis category based on the input analysis information; presenting a question related to the analysis category that does not satisfy the analysis condition and the user input information; The answer acquisition step acquires an answer from the user to the question, The analyzing step includes: Analyzing the answer to extract at least one keyword contained in the answer; Inferring to which of the analysis categories the keyword belongs; generating a pair of the keyword and the analysis category as the answer analysis information; The user analysis support method according to claim 8. (Appendix 10) The user analysis support method according to claim 9, wherein the analysis step includes determining characteristic words for each of the categories for analysis from the keywords estimated to belong to the categories for analysis based on at least one of the input analysis information and the response analysis information, and generating pairs of the categories for analysis and the characteristic words as analysis information of the subject. (Appendix 11) The user analysis support method according to any one of appendices 7 to 10, wherein the analysis step generates analysis information that maps features of the subject based on at least one of the input analysis information and the response analysis information. (Appendix 12) A user analysis step and a target selection step are included; The user analysis step includes a user analysis support method according to any one of Supplementary Notes 7 to 11, The target selection step selects at least one target appropriate for the user based on the analysis information generated by the user analysis step and target feature information. A target selection support method, wherein each of the steps is executed by a computer. (Appendix 13) The method includes a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step. The user input information acquisition step acquires user input information, the user input information includes a subject to be analyzed; The analysis step includes generating input analysis information by analyzing the user input information; the question presenting step presents a question based on the input analysis information; the answer acquisition step acquires an answer from the user to the question; The analysis step includes generating answer analysis information by analyzing the answer, The analysis step includes generating analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information; The output step outputs the analysis information. A user analysis support program for causing a computer to execute each of the above procedures. (Appendix 14) The analysis procedure includes: Analyzing the user input information to extract at least one keyword contained in the user input information; Inferring to which of at least one predetermined analytical category the keyword belongs; 14. The user analysis support program according to claim 13, which generates a pair of the keyword and the analysis category as the input analysis information. (Appendix 15) The question presentation step includes: determining whether an analysis condition is satisfied for each of the at least one analysis category based on the input analysis information; presenting a question related to the analysis category that does not satisfy the analysis condition and the user input information; the answer acquisition step acquires an answer from the user to the question; The analysis procedure includes: Analyzing the answer to extract at least one keyword contained in the answer; Inferring to which of the analysis categories the keyword belongs; generating a pair of the keyword and the analysis category as the answer analysis information; A user analysis support program as described in Appendix 14. (Appendix 16) The user analysis support program described in Appendix 15, wherein the analysis procedure determines characteristic words for each analysis category from the keywords estimated to belong to the analysis category based on at least one of the input analysis information and the response analysis information, and generates pairs of the analysis category and the characteristic words as analysis information of the subject. (Appendix 17) A user analysis support program according to any one of appendices 13 to 16, wherein the analysis procedure generates analysis information that maps features of the subject based on at least one of the input analysis information and the response analysis information. (Appendix 18) Including a user analysis procedure and a target selection procedure; The user analysis procedure is executed by a user analysis support program according to any one of appendices 13 to 17; The object selection step selects at least one object suitable for the user based on the analysis information generated in the user analysis step and object feature information. A user analysis support program for causing a computer to execute each of the above procedures. (Appendix 19) The method includes a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step. The user input information acquisition step acquires user input information, the user input information includes a subject to be analyzed; The analysis step includes generating input analysis information by analyzing the user input information; the question presenting step presents a question based on the input analysis information; the answer acquisition step acquires an answer from the user to the question; The analysis step includes generating answer analysis information by analyzing the answer, The analysis step includes generating analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information; The output step outputs the analysis information. A computer-readable recording medium having recorded thereon a user analysis support program for causing a computer to execute each of the above procedures. (Appendix 20) The analysis procedure includes: Analyzing the user input information to extract at least one keyword contained in the user input information; Inferring to which of at least one predetermined analytical category the keyword belongs; 20. The recording medium of claim 19, further comprising: a pair of the keyword and the analysis category generated as the input analysis information. (Appendix 21) The question presentation step includes: determining whether an analysis condition is satisfied for each of the at least one analysis category based on the input analysis information; presenting a question related to the analysis category that does not satisfy the analysis condition and the user input information; the answer acquisition step acquires an answer from the user to the question; The analysis procedure includes: Analyzing the answer to extract at least one keyword contained in the answer; Inferring to which of the analysis categories the keyword belongs; generating a pair of the keyword and the analysis category as the answer analysis information; 21. The recording medium according to claim 20. (Appendix 22) The recording medium described in Appendix 21, wherein the analysis procedure determines characteristic words for each analysis category from the keywords estimated to belong to the analysis category based on at least one of the input analysis information and the response analysis information, and generates pairs of the analysis category and the characteristic words as analysis information of the subject. (Appendix 23) 23. The recording medium of any one of appendices 19 to 22, wherein the analysis step generates analysis information that maps features of the subject based on at least one of the input analysis information and the response analysis information. (Appendix 24) Including a user analysis procedure and a target selection procedure; The user analysis procedure is executed by a user analysis support program according to any one of appendices 13 to 17; The object selection step selects at least one object suitable for the user based on the analysis information generated in the user analysis step and object feature information. A computer-readable recording medium having recorded thereon a user analysis support program for causing a computer to execute each of the above procedures. [Industrial Applicability]

[0089] The user analysis support device according to the present disclosure can support, for example, the analysis of true intentions that a user himself / herself is not aware of. Therefore, the present disclosure can be widely used in, for example, various business fields. [Explanation of symbols]

[0090] 10 User analysis support device (user analysis unit) 11 User input information acquisition section 12 Analysis Department 13 Question presentation section 14 Answer acquisition part 15 Analysis Department 16 Output section 101 CPU 102 Memory 103 Bus 104 Storage device 105 Input Device 106 Output Device 107 Communication Devices 20. Target Selection Support Device 21 Target Selection Division 201 CPU 202 Memory 203 Bus 204 Storage device 205 Input Device 206 Output Device 207 Communication Devices

Claims

1. The system includes a user input information acquisition unit, an analysis unit, a question presentation unit, an answer acquisition unit, an analysis unit, and an output unit, The user input information acquisition unit acquires user input information, the user input information includes a subject to be analyzed; The analysis unit generates input analysis information by analyzing the user input information, The question presenting unit presents a question based on the input analysis information; the answer acquisition unit acquires an answer from the user to the question, The analysis unit generates answer analysis information by analyzing the answers, The analysis unit generates analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information, The output unit outputs the analysis information.

2. The analysis unit is Analyzing the user input information to extract at least one keyword contained in the user input information; Inferring to which of at least one predetermined analytical category the keyword belongs; 2. The user analysis support device according to claim 1, wherein a pair of the keyword and the analysis category is generated as the input analysis information.

3. The question presentation unit, determining whether an analysis condition is satisfied for each of the at least one analysis category based on the input analysis information; presenting a question related to the analysis category that does not satisfy the analysis condition and the user input information; the answer acquisition unit acquires an answer from the user to the question, The analysis unit is Analyzing the answer to extract at least one keyword contained in the answer; Inferring to which of the analysis categories the keyword belongs; generating a pair of the keyword and the analysis category as the answer analysis information; 3. The user analysis support device according to claim 2.

4. 4. The user analysis support device of claim 3, wherein the analysis unit determines characteristic words for each of the categories for analysis from the keywords estimated to belong to the categories for analysis based on at least one of the input analysis information and the response analysis information, and generates pairs of the categories for analysis and the characteristic words as analysis information of the subject.

5. The user analysis support device according to claim 1 , wherein the analysis unit generates analysis information in which features of the subject are mapped based on at least one of the input analysis information and the response analysis information.

6. A user analysis unit and a target selection unit are included, The user analysis unit includes the user analysis support device according to any one of claims 1 to 4, The target selection unit selects at least one target appropriate for the user based on the analysis information generated by the user analysis unit and target feature information.

7. The method includes a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step, The user input information acquiring step acquires user input information, the user input information includes a subject to be analyzed; The analyzing step includes generating input analysis information by analyzing the user input information, The question presenting step presents a question based on the input analysis information, The answer acquisition step acquires an answer from the user to the question, The analysis step includes generating answer analysis information by analyzing the answers, The analysis step generates analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information, The output step outputs the analysis information. A user analysis support method, wherein each of the steps is executed by a computer.

8. A user analysis step and a target selection step are included; The user analysis step includes the user analysis support method according to claim 7, The target selection step selects at least one target appropriate for the user based on the analysis information generated by the user analysis step and target feature information. A target selection support method, wherein each of the steps is executed by a computer.

9. The method includes a user input information acquisition step, an analysis step, a question presentation step, an answer acquisition step, an analysis step, and an output step. The user input information acquisition step acquires user input information, the user input information includes a subject to be analyzed; The analysis step includes generating input analysis information by analyzing the user input information; the question presenting step presents a question based on the input analysis information; the answer acquisition step acquires an answer from the user to the question; The analysis step includes generating answer analysis information by analyzing the answer, The analysis step includes generating analysis information by analyzing a theme included in the user input information based on at least one of the input analysis information and the response analysis information; The output step outputs the analysis information. A user analysis support program for causing a computer to execute each of the above procedures.

10. Including a user analysis procedure and a target selection procedure; The user analysis step is executed by a user analysis support program according to claim 9, The object selection step selects at least one object suitable for the user based on the analysis information generated in the user analysis step and object feature information. A user analysis support program for causing a computer to execute each of the above procedures.

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