Collaborative community provision device

Abstract

To provide a collaborative community consisting of decentralized, self-governing organizations without the need for a centralized administrator or central authority.SOLUTION: A collaborative community provision device 1 includes: an extraction unit 114 for extracting registrant information and personal evaluation information of a registrant 4 who has a specialized field necessary for solving a problem from a personal evaluation database 121, and extracting group information and group evaluation information of a group capable of solving the problem from a group evaluation database 122; a request destination notification unit 113 for notifying the registrant 4 extracted by the extraction part 114 of the fact that the registrant has been selected as a request destination for solving the problem, together with the personal evaluation information; and an evaluation update unit 112 for evaluating the solution ability of the group working on the problem and the processing ability of the registrant 4 belonging to the group, respectively and updating the group evaluation database 122 and the personal evaluation database 121.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a collaborative community providing apparatus. [Background technology]

[0002] Patent Document 1 discloses a technology in which a department designation reception processing means 31 accepts input of the department to be checked after an assignment process for personnel transfer, and a department-specific suitability determination processing means 32 uses the personal characteristic data of each employee stored in a personal characteristic table 64 and the department characteristic data of the department to be checked stored in a department characteristic table 65 to determine the suitability of each employee assigned to the department to be checked for the department to be checked, and a department-specific alarm display processing means 33 displays a department-specific alarm on the screen indicating characteristic non-compliance for employees who are determined to have personal characteristics that deviate from the department characteristics of the department to be checked.

[0003] According to the technology of Patent Document 1, it is possible to carry out appropriate personnel transfers between the various departments that make up an organization. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2005-285021 A Summary of the Invention [Problem to be solved by the invention]

[0005] Incidentally, the technology of Patent Document 1 is a centralized management method in which the manager decides to assign each employee to a department based on the results of a judgment of the suitability of the employee's personal characteristics and department characteristics to the department. Therefore, each employee is not informed of the decision to transfer to the department by the manager, and is not able to consider or judge the suitability of the transfer while being conscious of his or her own suitability, so there is room for improvement in terms of motivation.

[0006] The present invention has been made in consideration of the above circumstances, and its purpose is to provide a collaborative community providing device that can conduct its own deliberations and make decisions by building a collaborative community consisting of decentralized autonomous organizations that do not require a centralized administrator or central authority. [Means for solving the problem]

[0007] As a result of intensive research into solving the above problems, the inventors have found that the above object can be achieved by notifying registered users that they have been selected as a party to request solutions to their problems, together with their personal evaluation information and group evaluation information. The inventors have then completed the present invention. Specifically, the present invention provides the following.

[0008] The present invention provides a personal evaluation database in which registrant information including personal identification information for identifying a registrant and personal evaluation information indicating processing capabilities in a specialized field of each of the registrants are associated with each other and stored in an updatable manner; a group evaluation database in which group information including group identification information identifying a group of the registrants who have tackled a problem to be solved by a combination of a plurality of the fields of expertise, personal identification information of all the registrants who belong to the group, and group evaluation information indicating the group's ability to solve the problem are stored in an updatable manner in association with each other; an extraction unit that extracts, when a new problem occurs, registrant information and personal evaluation information of registrants who have a specialized field required for solving the problem from the personal evaluation database, and extracts group information and group evaluation information of a group that can solve the problem from the group evaluation database; a request destination notification unit that notifies the registrants extracted by the extraction unit that they have been selected as a request destination for solving the problem together with the individual evaluation information, and that notifies the registrants belonging to the group extracted by the extraction unit that they have been selected as a request destination for solving the problem together with the individual evaluation information and the group evaluation information; an evaluation update unit that evaluates the solving ability of the group that tackled the problem and the processing ability of the registered person who belongs to the group, and updates the group evaluation database and the individual evaluation database; It is a collaborative community providing device having the above.

[0009] According to the above configuration, when a group consisting of multiple registrants tackles a problem, the group's problem-solving ability is evaluated as group evaluation information, and the processing ability of each individual registrant belonging to the group is evaluated as individual evaluation information. This group evaluation information and individual evaluation information are used to select a party to be asked to solve a new problem, and the fact that they have been selected as a party to be asked is notified together with the group evaluation information and individual evaluation information. Then, by receiving the group evaluation information and individual evaluation information, the registrant who has been notified can independently consider and decide whether to participate in the problem, while being conscious of their suitability. In other words, according to the above configuration, a platform for a collaborative community consisting of a decentralized autonomous organization that does not require a centralized administrator or central institution is constructed, and the registrants themselves can consider and decide whether to participate in the problem. Effect of the Invention

[0010] According to the present invention, a collaborative community consisting of decentralized autonomous organizations that do not require a centralized administrator or central authority is constructed, allowing registrants themselves to consider and decide whether or not to participate in a challenge. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is an explanatory diagram showing the flow of information between a collaborative community providing apparatus and each terminal of the present embodiment. [Diagram 2] FIG. 2 is a block diagram showing an example of a hardware configuration of the collaboration community providing device of this embodiment. [Diagram 3] FIG. 3 is an explanatory diagram showing the flow of information between the search tag adding unit and each unit. [Figure 4] FIG. 4 is an explanatory diagram showing the flow of information between the registrant information estimation unit and each unit. [Diagram 5] FIG. 5 is an explanatory diagram showing a state in which data is stored in the personal evaluation database. [Figure 6] FIG. 6 is an explanatory diagram showing a state in which data is stored in the group evaluation database. [Figure 7] FIG. 7 is an explanatory diagram showing a state in which data is stored in the SNS database. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an example of an embodiment of the present invention will be described in detail with reference to the drawings. (Collaborative Community Provisioning Device 1) As shown in Figure 1, the collaborative community providing device 1 is configured to build a collaborative community platform consisting of a decentralized autonomous organization that does not require a centralized administrator or central institution, and to notify registrants 4 that they have been selected as a party to be asked to solve a problem, along with personal evaluation information and group evaluation information.

[0013] As a specific example, the database has an individual evaluation database 121 in which registrant information including personal identification information identifying registrants 4 and personal evaluation information indicating the processing ability of each registrant 4 in his / her field of expertise are associated and stored in an updatable manner, and a group evaluation database 122 in which group information including group identification information identifying a group of registrants 4 who have worked on a problem that can be solved by multiple combinations of fields of expertise, and personal identification information of all registrants 4 who belong to the group are associated and stored in an updatable manner.

[0014] Here, a "registrant 4" is a person who has registered for the services of the collaborative community providing device 1, and is given personal identification information unique to the registrant 4 by registering initial setting information such as a name and a field of expertise (skills). If the registrant belongs to a group, a combination of a group identification number and a personal identification number is given. Therefore, if the registrant 4 belongs to multiple groups, group identification information is given for each group, and the registrant will have an identification number that is a combination of a group identification number and a personal identification number for each group to which the registrant belongs. The registrants 4 include people who work for companies, as well as students, housewives, the unemployed, freelancers, and self-employed people. Furthermore, since the services of the collaborative community providing device 1 are provided through an information and communication network 5 such as the Internet, anyone can register and use the services, regardless of nationality or place of residence, except in cases where there are restrictions under the terms of use.

[0015] "Personal identification information" is personal information for identifying a registrant 4. When registering initial setting information, the individual may input a real name, a nickname, etc. as personal identification information, or the collaborative community providing device 1 may automatically assign it. In this embodiment, a case will be described in which it is automatically assigned as P001 or P002. "Registrant information" includes the registrant's name, contact information, gender, date of birth, registration date, etc. "Field of expertise" refers to a specific area or field in which a person has specific knowledge, skills, and experience and can demonstrate specialized knowledge and ability. For example, in the IT (Information Technology) field, examples include programming, data analysis, content production, and cybersecurity.

[0016] The "personal evaluation information" is information that objectively evaluates the expertise and abilities of the registrant 4. In this embodiment, the evaluation is shown in a five-point scale, but is not limited to this. The personal evaluation information is obtained based on evaluation factors such as an evaluation of the ability in a specialized field, an evaluation of achievements and results, qualification information, cooperativeness, and leadership. The evaluation is preferably performed by the large-scale language model of the natural language generation system 2 in FIG. 2, with the evaluation factors and the quantification of the evaluation as prompt information. In this way, the personal evaluation information is given according to the abilities and contributions in a group, and can be used to assign appropriate roles and responsibilities. In addition, the personal evaluation information can be used as an index of skills, abilities, achievements, etc. as a portfolio representing an individual's abilities, and can also be used to appeal one's abilities when job hunting or changing jobs.

[0017] A "problem" is something that is solved by a combination of multiple fields of expertise, and examples of the problem include social problems, technical problems, educational problems, health problems, and political problems. In this embodiment, as specific examples of technical problems, game creation, data analysis, interface design, promotion, and game security are exemplified as Internet-related problems. For example, a game creation problem is exemplified as a combination of the fields of expertise of programming, design, and project management, that is, multiple people with expertise in three fields are required for solving the problem. Also, a data analysis problem is exemplified as a combination of the fields of expertise of data analysis and programming, that is, people with expertise in two fields are required for solving the problem. It is preferable that a level of difficulty is added to the problem. This is because it can be used as a criterion for the registrant 4 to decide whether or not to participate (apply).

[0018] A "collection" is a group or community of multiple registrants 4 with different areas of expertise that are formed to find solutions to a specific problem together. The expertise and skills of each registrant 4 in a group may overlap. For example, three people who specialize in data analysis may belong to one group. In addition, a group is formed by a collaborative community consisting of a decentralized autonomous organization that does not require a centralized administrator or central institution, so the registrants 4 gather together voluntarily. In such a group of registrants 4, each registrant 4 has a different area of ​​expertise and skill, so each registrant 4 can tackle the problem by utilizing his or her own expertise and ability. This allows multiple registrants 4 with different backgrounds and skills to cooperate and collaborate, share information and ideas, and propose solutions, making it possible to derive more effective solutions. In addition, if a registrant 4 belongs to a company, he or she can have an opportunity to improve his or her skills outside the company.

[0019] "Group identification information" is information for identifying a group. When a group is formed, the registered members 4 belonging to the group may set a name, nickname, etc. as group identification information, or the collaborative community providing device 1 may automatically assign it. In this embodiment, a case where it is automatically assigned as G1 or G2 is described. "Group information" is general information about the group, including group identification information. Group information includes information about the group, such as the group's name, group purpose, and group activities. For example, the group's name may be "environmental problem solving project," the group's purpose may be "solving global warming," and the group's activities may be "reducing greenhouse gases that cause global warming, developing renewable energy, and promoting environmental education."

[0020] "Group evaluation information" is information for evaluating the solving ability and results of a group of registrants 4 who have worked on a specific task. The group evaluation information is obtained based on information such as the group's goals and evaluation criteria for the task, and the evaluations and feedback comments between the registrants 4. Specifically, evaluation elements such as the degree of completion of the task, the quality of the results, the use of knowledge and skills, teamwork, and cooperation are taken into consideration comprehensively. As a result, the group evaluation information visualizes the group's contribution to the task and can be used as an index of the group's level of solving ability for what types of tasks. The evaluation is preferably performed by the large-scale language model of the natural language generation system 2 in FIG. 2, with the evaluation elements and the quantification of the evaluation as prompt information.

[0021] The individual evaluation database 121 and the group evaluation database 122 are stored in the storage unit 12. The storage unit 12 is connected to the control unit 11 so as to be able to communicate data with the control unit 11. The control unit 11 has an extraction unit 114 that extracts, when a new problem occurs, registrant information and individual evaluation information of registrants 4 who have a specialized field necessary for solving the problem from the individual evaluation database 121, and extracts group information and group evaluation information of a group capable of solving the problem from the group evaluation database 122, a request destination notification unit 113 that notifies the registrants 4 extracted in the extraction unit 114 that they have been selected as a request destination for solving the problem together with the individual evaluation information and notifies the registrants 4 who belong to the group extracted in the extraction unit 114 that they have been selected as a request destination for solving the problem together with the individual evaluation information and the group evaluation information, and an evaluation update unit 112 that evaluates the solving ability of the group that tackled the problem and the processing ability of the registrants 4 who belong to the group, and updates the group evaluation database 122 and the individual evaluation database 121.

[0022] According to the above configuration, when a group consisting of multiple registrants 4 tackles a problem, the group's problem-solving ability is evaluated as group evaluation information, and the processing ability of each registrant 4 belonging to the group is evaluated as individual evaluation information. The group evaluation information and individual evaluation information are used to select a party to be asked to solve a new problem, and the fact that the registrant 4 has been selected as a party is notified together with the group evaluation information and individual evaluation information. Then, the registrant 4 who receives the notification can independently consider and decide whether to participate in the problem while being conscious of his / her suitability by receiving the group evaluation information and individual evaluation information. In other words, according to the above configuration, a platform for a collaborative community consisting of a decentralized autonomous organization that does not require a centralized administrator or central institution is constructed, and the registrant 4 himself / herself can consider and decide whether to participate in the problem.

[0023] Furthermore, the collaborative community providing device 1 has a community unit 111. The community unit 111 is configured to collect information from user terminals 3 operated by registered persons 4 and unregistered users. As a result, for example, when a plurality of registered persons 4 form a group to solve a certain problem, information such as conversations and materials between the registered persons 4 of this group is collected and stored in a database (not shown), so that it can be used to evaluate the group during and after the problem is solved, and to evaluate each of the registered persons 4 individually.

[0024] As shown in FIG. 2, the collaborative community providing device 1 has a value imparting unit 117 that imparts to the registrant 4 a value according to the magnitude of the processing ability according to the individual evaluation information and a value according to the magnitude of the problem-solving ability according to the group evaluation information. Here, the "value" is not particularly limited as long as it is something that benefits the registrant 4. For example, the value may be monetary value, digital currency points, crypto assets, or real goods, services, or gift cards. Furthermore, examples of the value include privileges and benefits such as a specific position, authority, and access right, promotional opportunities to advertise oneself or one's skills, opportunities to acquire more advanced skills and knowledge, and opportunities for training and instruction. According to the above configuration, the motivation of the registrant 4 can be increased by imparting to the registrant 4 a value according to the magnitude of the processing ability according to the individual evaluation information and a value according to the magnitude of the problem-solving ability according to the group evaluation information.

[0025] The collaborative community providing device 1 also has a token recording unit 118 that converts the individual evaluation information and group evaluation information into non-fungible tokens that cannot be transferred to others and records them on the blockchain 7, i.e., makes them on-chain. As a result, the collaborative community providing device 1 converts the individual evaluation information and group evaluation information, together with the individual identification information and group identification information, into a soul band token (SBT) that cannot be transferred to others and is recorded on the blockchain 7 by the token recording unit 118, so that the individual evaluation information and group evaluation information can be proved with higher reliability than when they are stored only in a database. Note that the blockchain 7 may record activity histories of groups and individuals, search tags, and the like, in addition to the individual evaluation information and group evaluation information.

[0026] Here, a "non-fungible token" is a digital token that represents a specific asset issued on the blockchain 7. Non-fungibility means that the token is not exchangeable for other tokens. "Blockchain 7" is a distributed digital ledger technology. Data is divided into continuous data structures called blocks, and each block is linked to form a chain. Each block contains individual evaluation information and collective evaluation information, which are multiple transactions, and these data are recorded on the blockchain 7. Blockchain 7 is operated on a distributed network, and new data (individual evaluation information and collective evaluation information) is added or changed based on the agreement between participants who perform mining.

[0027] "Soul Band Token (SBT)" is a token used to record individual and group evaluation information on the blockchain as a non-fungible token. Soul Band Token makes it possible to prove and protect the information by tokenizing the evaluation information of individuals and groups. As a result, individual and group evaluation information is permanently recorded on the blockchain and cannot be tampered with or transferred to others, improving reliability and security and providing high reliability at the time of proof.

[0028] 3, the collaborative community providing device 1 has a search tag assigning unit 119. The search tag assigning unit 119 is capable of data communication with the SNS system 8 and the natural language generation system 2, and stores search tags generated by the natural language generation system 2 in the SNS database 123. The search tag assigning unit 119 has a search tag prompt forming unit 1191 and a search tag evaluation unit 1192. The search tag prompt forming unit 1191 has a function of collecting transmitted information such as comments made by each registrant 4 from the SNS system 8 based on the registrant information and group information received from the individual evaluation database 121 and the group evaluation database 122, and executing a process of rewriting the transmitted information into prompt information for generating appropriate search tags as a prompt for a large-scale language model of the natural language generation system 2. The search tag evaluation unit 1192 has the function of determining whether the search tag received from the natural language generation system 2 is appropriate, and if it is not appropriate, causing the search tag prompt formation unit 1191 to reprocess the prompt information and send it to the natural language generation system 2, while if it is appropriate, causing the search tag to be associated with the identification information of the registrant 4 and stored in the SNS database 123.

[0029] In this way, when the search tag assignment unit 119 assigns search tags for estimating the specialty of the registrant 4 to the posted information used by the registrant 4 in interacting with others through the social networking service of the SNS system 8, it accesses the natural language generation system 2, learns the statistical structure of language based on training data, and generates new sentences using the learning results, by making a large-scale language model respond to the posted information as the content of the prompt, thereby generating search tags.

[0030] Here, a "social networking service (SNS)" is a platform for users to interact with each other and share information and content on an information and communication network 5 such as the Internet. In general, it enables users to create personal profiles, connect with friends and followers, and exchange information and interact through activities such as posting and commenting. Representative social networking services include Facebook (registered trademark), Twitter (registered trademark), and Instagram (registered trademark).

[0031] "Outgoing information" refers to information posted or shared by a registrant 4 about himself / herself, his / her interests and activities. Specifically, outgoing information includes profile information (such as self-introduction and career history), posted text and photos, shared links and videos, and commented content. Through such outgoing information, the registrant's hobbies, interests, fields of expertise, activities, etc. may be revealed. "Search tags" refer to labels or keywords that classify and organize information and make it searchable by specific keywords or categories. When searching for people knowledgeable in a specific technical field or searching for posts related to a specific topic, related search tags can be used as search keywords. In this way, by adding search tags to the outgoing information of a registrant 4, it becomes easier to find information related to the registrant's field of expertise.

[0032] According to the above configuration, when registrant information and fields of expertise are newly stored in the personal evaluation database, search tags for estimating the fields of expertise are generated using a large-scale language model and added to the transmitted information, thereby improving the objectivity and accuracy of estimating the fields of expertise using search tags.

[0033] In addition, since the large-scale language model learns the statistical structure of language from training data and generates new sentences using the learning results, appropriate search tags can be automatically generated based on the information transmitted by the registrant 4. This eliminates the need to manually assign search tags, making tagging more efficient. Furthermore, since the large-scale language model is trained using large-scale training data, it can learn a variety of expressions and contexts. This increases the likelihood that more accurate and appropriate search tags will be generated, making it more likely that the search tags will reflect useful keywords and categories for estimating the specialty of the registrant 4. Furthermore, since similar search tags are more likely to be assigned to transmitted information related to the same specialty, consistent tagging is possible, improving the efficiency of information organization and search.

[0034] 4, the collaborative community providing device 1 has a registrant information estimating unit 116. The registrant information estimating unit 116 is capable of data communication with the SNS system 8 and the natural language generation system 2, and stores information on the person definition of the registrant 4 and the degree of interest in various tasks generated by the natural language generation system 2 in the personal evaluation database 121. The registrant information estimating unit 116 has a person estimation prompt forming unit 1161 and a person estimation evaluation unit 1162. The person estimation prompt forming unit 1161 has a function of collecting transmission information such as comments made by each registrant 4 from the SNS system 8 based on the registrant information received from the personal evaluation database 121, and executing a process of rewriting the transmission information into prompt information for generating an appropriate person definition and degree of interest as a prompt for a large-scale language model of the natural language generation system 2. The person estimation evaluation unit 1162 has the function of determining whether the person definition and interest level received from the natural language generation system 2 are appropriate, and if they are not appropriate, causing the person estimation prompt formation unit 1161 to reprocess the prompt information and send it to the natural language generation system 2, while if they are appropriate, causing the person definition and interest level to be associated with the identification information of the registrant 4 and stored in the personal evaluation database 121.

[0035] In this way, when the registrant information estimation unit 116 infers the person definition of the registrant 4 and the degree of interest in various tasks based on the transmitted information used by the registrant 4 in interacting with others through the social networking service of the SNS system 8 and includes the inference in the registrant information, it accesses the natural language generation system 2, learns the statistical structure of language based on training data, and generates new sentences using the learning results, by making the large-scale language model respond to the transmitted information as the content of the prompt, thereby generating the person definition of the registrant 4 and the degree of interest in various tasks.

[0036] Here, "person definition" refers to information that represents the personal attributes and characteristics of registrant 4, such as the individual characteristics, personality, interests, concerns, and behavioral tendencies of that person. "Level of interest in various issues" is an index that represents how interested registrant 4 is in a particular issue or topic.

[0037] According to the above configuration, since the large-scale language model learns the statistical structure of language based on the training data, individual characteristics and tendencies can be extracted based on the transmitted information of the registrant 4, and a person definition can be generated. For example, from the content of posts and the tendency of comments, characteristics such as whether the registrant 4 is proactive, passive, logical, or conservative can be inferred. In addition, since the large-scale language model can generate new sentences using the learning results, sentences generated based on transmitted information may reflect topics and issues related to the interests and concerns of the registrant 4. This makes it possible to infer what issues the registrant is interested in and what fields he or she is interested in. And, by using the large-scale language model, the person definition of the registrant 4 and the degree of interest in various issues obtained in this way have higher objectivity and accuracy than when set by humans.

[0038] 2, the collaborative community providing device 1 has a group estimation unit 115 that trains a machine learning model using as teacher data the tasks undertaken by a group of registrants 4, group evaluation information of the group who undertook the tasks, and the person definitions of registrants 4 and their degrees of interest in various tasks, and estimates a group of registrants 4 with the highest evaluation value for the group evaluation information when a new task is input to the machine learning model. Note that the group estimation unit 115 may estimate a group of registrants 4 whose evaluation in the group evaluation information is within the top several percent of the entire group.

[0039] Specifically, a plurality of input elements including tasks tackled by a group of registered users 4, the person definition of registered users 4, and the degree of interest in various tasks are prepared as training data. Then, a multi-layered neural network is constructed by learning using the input elements prepared as training data and the group evaluation, which is an output value corresponding to the input elements, and learning is advanced so that the data input to the input layer is processed in the hidden layer, and finally the group evaluation is predicted in the output layer. During learning, a data set of the input elements and the group evaluation is divided into training data and test data, a model for prediction and classification is trained using the training data, and the learning accuracy is confirmed by evaluating the performance using the test data. Then, the trained machine learning model is used to input tasks tackled by a new group of registered users 4, the person definition, and the degree of interest in various tasks, and the predicted value of the group evaluation is output, thereby obtaining the group evaluation. Then, the predicted value of the group evaluation is obtained using various combinations of input elements, and a group showing the highest predicted value or a value within the top few percent, and the registered users 4 who constitute this group are identified.

[0040] According to the above configuration, when selecting registrants 4 who will tackle a new task, a group of registrants who demonstrate considerably high abilities can be estimated by machine learning. This makes it possible to form a group that is likely to include registrants 4 who are interested in a particular task, so that registrants 4 who are working on related tasks can gather together and collaborate and share information more effectively. In addition, by using a machine learning model, hidden correlations and features can be extracted by learning correlations between features based on training data, and it may be possible to estimate a group that takes unexpected associations and factors into account. Furthermore, by using a machine learning model, manual work and subjective judgments for processing large amounts of data and complex features are eliminated, and a group can be objectively estimated through a statistical approach.

[0041] As described above, when the machine learning model is trained using the tasks performed by the group of registered users 4, the group evaluation information of the group who performed the tasks, and the person definition and the degree of interest in various tasks of the registered users 4 as teacher data, it is preferable that the collaborative community providing device 1 generates a conversation between avatars imitating the utterance tendency of the registered users 4 based on the person definition and the degree of interest. The generation of the conversation is realized by, for example, first matching two or more registered users 4 who have similar characteristics in part or all based on the characteristics of the registered users 4 such as information, experience, and cases they are working on, and then using the machine learning model that has been trained as described above, executing a first conversation generation step of generating a trigger utterance by providing a topic exemplified by the above-mentioned tasks and information identifying one registered user 4 as input, and then repeatedly executing a second conversation generation step of generating a utterance that responds to the utterance provided as input by providing the utterance generated by the first conversation generation step or the like as a further input and imitating the utterance tendency of another registered user 4 different from the registered user 4 related to the utterance. The second conversation generation step is repeated until a given number of conversations, for example, two to four, have been generated, or until an instruction to stop conversation generation is received from a registrant 4. The number of registrants 4 involved in conversation generation is not particularly limited as long as it is two or more, and may be, for example, two or three or more, or the number of registrants 4 belonging to the above-mentioned group, etc.

[0042] The collaboration community provided by the collaboration community providing device 1 of the present embodiment may include registrants 4 who are reluctant to contact and / or collaborate with other registrants 4 because they do not know the personalities of the other registrants 4. If such registrants 4 can be given an opportunity to contact other registrants 4 who are matched with them, the collaboration community will be further activated. According to the above configuration, the collaboration community providing device 1 can automatically generate a conversation on a specific topic (e.g., "AI business negotiation") between avatars based on the profiles of the registrants 4 and provide it to the registrants 4. The collaboration community providing device 1 can then provide an opportunity for the registrants 4 who find the content of the conversation interesting to directly contact the other registrants 4 involved in the conversation via messages, web meetings, or the like, and collaborate with them. In addition, if the conversation includes a new idea that the registrants 4 do not have, providing the conversation can provide the registrants 4 with an opportunity to start a new collaboration based on the new idea. Therefore, by generating the above-described conversation, the collaborative community providing apparatus 1 can realize a collaborative community in which each registrant 4 can consider and make decisions based on the generated conversation and can keep in contact with other registrants 4.

[0043] The individual evaluation database 121, the group evaluation database 122, and the SNS database 123 are stored in the storage unit 12. The storage unit 12 is connected to the user terminal 3, the requester terminal 6, the blockchain 7, the natural language generation system 2, and the SNS system 8 in a data communicable manner via the communication unit 13 provided in the collaborative community providing device 1 and an information and communication network 5 such as the Internet. The requester terminal 6 is a terminal operated by a requester who provides a task. Examples of the requester include corporate managers, project managers, startup founders, individual researchers, and experts. The storage unit 12 may be a data server connected to the information and communication network 5, separate from the collaborative community providing device 1. The storage unit 12 may be composed of a plurality of data servers provided for the individual evaluation database 121 and the group evaluation database 122. Examples of the user terminal 3 and the requester terminal 6 include general stationary information processing devices, smartphones, tablet terminals, and other mobile terminal devices.

[0044] Furthermore, the collaboration community providing device 1 has an input device 15 connected to the input receiving unit 1112 and a display device 14 connected to the display control unit 1111. Examples of the input device 15 include a keyboard, a mouse, a touch panel, and a voice input device. Examples of the display device 14 include a liquid crystal display device. This allows the collaboration community providing device 1 to be configured with an information processing device such as a general personal computer, a laptop computer, a smartphone, or a tablet terminal. The collaboration community providing device 1 may lack at least one of the input device 15 and the display device 14. In this case, since the input device 15 and the display device 14 are provided in an external terminal (not shown), the collaboration community providing device 1 can be used as a collaboration community providing server. The collaboration community providing device 1 may also be configured by cloud computing. In this case, the collaboration community providing device 1 is constructed on the cloud, so that it can flexibly respond to an increase in the number of registered users 4 and an increase in the amount of data, and since multiple servers and data centers can be used in a cloud environment, even if a failure occurs, backup or redundant resources are automatically switched over, and interruptions to services can be minimized.

[0045] (Database) As shown in FIG. 5, the personal evaluation database 121 has a personal identification information item, a registrant name item, a specialty (skill) item, a personal evaluation item, a person definition item, and an interest field item, which are associated with each other. The personal identification information item is an identifier for uniquely identifying each registrant 4, and corresponds to, for example, P001, P002, and the like. The registrant name item is the name of the registrant 4, and corresponds to, for example, Yamada Taro, Tanaka Hanako, and the like. The specialty (skill) item is the specialty field or skill of each registrant 4, and corresponds to, for example, programming, design, project management, and the like. The personal evaluation item is personal evaluation information of each registrant 4, and an evaluation value such as 4.5 / 5 or 4.2 / 5 is input. The person definition item is information on the person definition and characteristics of each registrant 4, and for example, characteristics such as proactive, cooperative, sensitive, and creative are described. The interest field items are information on the areas of interest or concerns of each registrant 4, such as technology news, games, art, design, business strategy, and team management.

[0046] As a result, the personal evaluation database 121 accumulates characteristic information such as personal information, skills, evaluations, definitions, and areas of interest for each registrant 4, making it possible to select an appropriate registrant 4 based on the characteristic information of each registrant 4 when a new task arises.

[0047] As shown in FIG. 6, the group evaluation database 122 has group items, assignment items, skill items, group evaluation items, and individual identification information items in association with each other. The group items are identifiers of each group, such as G1 and G2. The assignment items are names of assignments or projects that each group tackles, such as game creation, data analysis, and interface design. The skill items are skills and specialized knowledge required by each group, such as programming, design, and project management. The group evaluation items are evaluations of the problem-solving capabilities of each group, such as 4.5 or 4.2. The individual identification information items are identification information of individuals belonging to each group, such as P001, P002, and P003.

[0048] In this way, the individual evaluation database 121 accumulates information such as the issues and necessary skills for each different group, evaluation of problem-solving ability, and information on the individuals who belong to the group, making it possible to identify registrants 4 with appropriate skill sets and problem-solving abilities according to the goals and needs of each group. Note that groups that are displayed as "Recruiting" indicate that registrants 4 to become members of the group are still being recruited, and personal identification information has not yet been specified.

[0049] 7, the SNS database 123 has a personal identification information item, a registrant name item, and a search tag item in association with each other. The SNS database 123 can be updated by the search tag assignment unit 119. The search tag item is information on specific tags or keywords associated with each individual, and if there are multiple tags, they are separated by commas. For example, this applies to development, analysis, graphics, UI (user interface), UX (user experience), etc.

[0050] This makes it possible for the SNS database 123 to be used for purposes such as understanding the characteristics and skills of individual registrants 4, assigning related projects and tasks, and building teams. By searching and filtering registrants 4 based on specific tag information, it can be used as a clue to find suitable talent.

[0051] The above databases 121, 122, 123 may be stored in a single storage unit 12, or may be distributed and stored in multiple data servers. When the databases 121, 122, 123 are distributed and stored in multiple data servers, the load required for information update processing can be reduced even when there are a large number of registrants 4 or groups.

[0052] (Collaborative Community Offering Program) 2 may be configured as either hardware or software. These units 111-119 constitute at least a part of the control unit 11. When the units 111-119 are configured as software, the control unit 11 is made to execute a collaboration community providing program that provides a collaboration community consisting of a distributed autonomous organization to a plurality of registrants 4.

[0053] Specifically, the collaborative community providing program of the collaborative community providing device 1 includes an individual evaluation database 121 in which registrant information including personal identification information for identifying the registrant 4 and personal evaluation information indicating the processing ability in the specialized field of each of the registrants 4 are associated and stored in an updatable manner, and a group evaluation database 122 in which group information including group identification information for identifying a group of registrants 4 who have worked on a problem to be solved by a combination of multiple specialized fields and group evaluation information indicating the group's problem-solving ability are associated and stored in an updatable manner. The collaborative community providing program of the collaborative community providing device 1 includes an individual evaluation database 121 in which registrant information including personal identification information for identifying the registrant 4 and personal evaluation information indicating the processing ability in the specialized field of each of the registrants 4 are associated and stored in an updatable manner, and the collaborative community providing program causes the control unit 11, a computer, to The process executes an extraction processing step in which registrant information and personal evaluation information are extracted from the personal evaluation database 121, and group information and group evaluation information of groups capable of solving the problem are extracted from the group evaluation database 122; a request destination notification processing step in which the registrants 4 extracted in the extraction processing step are notified, along with the personal evaluation information, that they have been selected as a party to be asked to solve the problem, and the registrants 4 who belong to the group extracted in the extraction processing step are notified, along with the personal evaluation information and the group evaluation information, that they have been selected as a party to be asked to solve the problem; and an evaluation update processing step in which the solving ability of the group that worked on the problem and the processing ability of the registrants 4 who belong to the group are respectively evaluated, and the group evaluation database 122 and the personal evaluation database 121 are updated.

[0054] In addition, the collaborative community providing program may cause the control unit 11, a computer, to execute one or more of the processing steps that realize the functions of the community unit 111, the group estimation unit 115, the registrant information estimation unit 116, the value assignment unit 117, the token recording unit 118, and the search tag assignment unit 119.

[0055] According to the above-described collaboration community providing program, simply by installing the program in an information processing device such as a personal computer or a tablet terminal, the information processing device can function as the collaboration community providing device 1. The collaboration community providing program may be distributed in a state recorded on a computer-readable recording medium such as a CD-ROM or a USB memory, or may be distributed via a two-way communication network or communication line such as the Internet or a one-way communication network such as a television broadcast.

[0056] (How to provide a collaborative community) A part or all of the processing steps in the collaboration community providing program may be configured by hardware. That is, the collaboration community providing device 1 may be configured to be able to execute the collaboration community providing method. To be more specific, the collaboration community providing method is executed in the collaboration community providing device 1 including: an individual evaluation database 121 in which registrant information including personal identification information identifying the registrant 4 and individual evaluation information indicating the processing ability in the specialized field of each of the registrants 4 are associated and updated and stored; and a group evaluation database 122 in which group information including group identification information identifying a group of the registrants 4 who have worked on a problem solved by a combination of multiple specialized fields, and personal identification information of all the registrants 4 who belong to the group and group evaluation information indicating the solving ability of the group for the problem are associated and updated and may include an extraction processing step, a request destination notification processing step, and an evaluation update processing step.

[0057] In addition, the collaborative community providing method may include one or more of the processing steps that realize the functions of the community unit 111, the group estimation unit 115, the registrant information estimation unit 116, the value assignment unit 117, the token recording unit 118, and the search tag assignment unit 119.

[0058] It should be noted that within the scope of the concept of the present invention, a person skilled in the art may come up with various modifications and alterations. It is understood that such modifications and alterations fall within the scope of the present invention. For example, even if a person skilled in the art appropriately adds, deletes, or modifies the design of the above-described embodiment, or adds, omits, or modifies the conditions of a process, these modifications and alterations are included in the scope of the present invention as long as they include the gist of the present invention. [Explanation of symbols]

[0059] 1 Collaborative community provision device 11 Control section 111 Community Department 112 Evaluation Update Division 113 Request Notification Department 114 Extraction part 115 Population Estimation Department 116 Registrant Information Estimation Department 117 Value Addition Department 118 Token Recording Unit 119 Search tagging section 12 Storage section 121 Personal Evaluation Database 122 Group Evaluation Database 123 Social Media Database 13. Communications Department 14 Display device 15 Input Devices 2. Natural Language Generation System 3. User terminal 4. Registrant 5. Information and Communications Network 6. Client terminal 7. Blockchain 8. Social Networking System

Claims

1. a personal evaluation database in which registrant information including personal identification information for identifying a registrant and personal evaluation information indicating processing capabilities in a specialized field possessed by each of the registrants are stored in an updatable manner in association with each other; a group evaluation database in which group information including group identification information identifying a group of the registrants who have tackled a problem to be solved by a combination of a plurality of the fields of expertise, personal identification information of all the registrants who belong to the group, and group evaluation information indicating the group's ability to solve the problem are stored in an updatable manner in association with each other; an extraction unit that extracts, when a new problem occurs, registrant information and personal evaluation information of registrants who have a specialized field required for solving the problem from the personal evaluation database, and extracts group information and group evaluation information of a group that can solve the problem from the group evaluation database; a request destination notification unit that notifies the registrants extracted by the extraction unit that they have been selected as a request destination for solving the problem together with the individual evaluation information, and that notifies the registrants belonging to the group extracted by the extraction unit that they have been selected as a request destination for solving the problem together with the individual evaluation information and the group evaluation information; an evaluation update unit that evaluates the solving ability of the group that tackled the problem and the processing ability of the registered person who belongs to the group, and updates the group evaluation database and the individual evaluation database; A collaborative community providing device having the above configuration.

2. The collaborative community providing device according to claim 1 , further comprising a value assigning unit that assigns to said registered users a value corresponding to the level of processing ability based on said personal evaluation information and a value corresponding to the level of problem-solving ability based on said group evaluation information.

3. When a search tag for estimating the specialty field of a registered person is added to information transmitted by the registered person used in exchange activities with others through a social networking service, The collaborative community providing device of claim 1, further comprising a search tag assignment unit that generates the search tags by making a large-scale language model that learns the statistical structure of language based on training data and generates new sentences using the learning results correspond to the transmitted information as the content of the prompt.

4. The collaborative community providing device according to claim 1 , further comprising a token recording unit that converts the personal evaluation information and the collective evaluation information into non-fungible tokens that cannot be transferred to others and records them on a blockchain.

5. When the person's personality and the degree of interest in various issues are inferred based on the information transmitted by the person in the social networking service used for exchange activities with others and included in the person's information, The collaborative community providing device of claim 1, further comprising a registrant information estimation unit that generates a person definition of the registrant and a degree of interest in various tasks by making a large-scale language model that learns the statistical structure of language based on training data and generates new sentences using the learning results correspond to the transmitted information as the content of the prompt.

6. The collaborative community providing device of claim 1 has a group estimation unit that trains a machine learning model using as teaching data the tasks undertaken by the group of registered individuals, group evaluation information of the group who undertook the tasks, and the person definitions of the registered individuals and their degrees of interest in various tasks, and when a new task is input into the machine learning model, estimates the group of registered individuals that has the highest evaluation value in the group evaluation information.

Images