Community-based collaborative knowledge system and community-based collaborative knowledge method

Abstract

To promote knowledge accumulation by increasing the incentive of a knowledge provider.SOLUTION: This knowledge storage support system collects knowledge from a knowledge provider, and determines whether the received knowledge is useful knowledge based on similarity between the received knowledge and the stored useful knowledge. The knowledge-based collaborative system calculates, for each knowledge provider, a royalty to the knowledge provider based on the number of pieces of useful knowledge provided by the knowledge provider.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates generally to supporting the accumulation of knowledge. [Background technology]

[0002] Accumulating knowledge on an individual basis requires a great deal of effort. For this reason, a technology has been devised that solicits ideas from an unspecified number of people and acquires the knowledge provided in response to the solicitation (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2023-005376 Summary of the Invention [Problem to be solved by the invention]

[0004] Patent Document 1 discloses a technology in which "when a viewer views at least a portion of the searched information, a fee is collected from the viewer and the fee is distributed to at least the questioner and the answerer of the relevant knowledge" (for example, paragraph 0009 of Patent Document 1).

[0005] However, according to the distribution method disclosed in Patent Document 1, the collected money is basically split between the questioner and the answerer, and the distribution is not very appropriate.As a result, the incentive for knowledge providers is low and knowledge accumulation is not promoted. [Means for solving the problem]

[0006] The knowledge accumulation support system solicits knowledge from knowledge providers, determines whether the accepted knowledge is useful knowledge based on the similarity of the accepted knowledge with accumulated useful knowledge, and calculates royalties for each knowledge provider based on the number of useful knowledges provided by that knowledge provider. [Effects of the Invention]

[0007] This increases the incentives for knowledge providers, thereby promoting knowledge accumulation. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram showing an overview of a process from knowledge collection to royalty payment realized by the present system, which is a knowledge accumulation support system according to an embodiment of the present invention. [Figure 2] 1 is a diagram illustrating a configuration example of a first embodiment of the present system. [Figure 3] FIG. 2 is a diagram illustrating an example of a database configuration in the first embodiment of the present system. [Figure 4] FIG. 1 is a diagram showing the relationship between types of knowledge that appear in this system. [Figure 5] 1 is a flowchart of knowledge selection in this system. [Figure 6] 10 is a flowchart of template creation in the present system. [Figure 7] 10 is a flowchart of royalty calculation in this system. [Figure 8] FIG. 10 is a diagram showing an example of a knowledge solicitation screen for the design drawing automatic checking tool of the present system. [Figure 9] FIG. 10 is a diagram showing an example of a knowledge input screen for the automatic design drawing checking tool of the present system. [Figure 10] FIG. 10 is a diagram showing an example of a template for the automatic design drawing check tool of the present system. [Figure 11] FIG. 10 is a diagram showing an example of a knowledge solicitation screen of a knowledge search tool of the present system. [Figure 12] FIG. 10 is a diagram showing an example of a knowledge input screen of a knowledge search tool of the present system. [Figure 13] FIG. 2 is a diagram illustrating an example of a template for a knowledge search tool of the present system. [Figure 14]FIG. 10 is a diagram illustrating a configuration example of the present system according to a second embodiment. [Figure 15] 10 is a flowchart of automatic creation of a template for an automatic design drawing check tool in the second embodiment of the present system. [Figure 16] 10 is a flowchart of automatic creation of a template related to a knowledge search tool in the second embodiment of the present system. [Figure 17] FIG. 2 is a diagram illustrating an example of a hardware configuration of the present system. DETAILED DESCRIPTION OF THE INVENTION

[0009] In the following description, an "interface apparatus" may refer to one or more interface devices, which may be at least one of the following: An I / O interface device is one or more I / O (Input / Output) interface devices. The I / O (Input / Output) interface devices are interface devices for at least one of an I / O device and a remote display computer. The I / O interface device for the display computer may be a communications interface device. The at least one I / O device may be a user interface device, for example, either an input device such as a keyboard and a pointing device, or an output device such as a display device. A communication interface apparatus that is one or more communication interface devices. The one or more communication interface devices may be one or more homogeneous communication interface devices (e.g., one or more NICs (Network Interface Cards)) or two or more heterogeneous communication interface devices (e.g., an NIC and an HBA (Host Bus Adapter)).

[0010] In the following description, "memory" refers to one or more memory devices, which are an example of one or more storage devices, and may typically be a primary storage device. At least one memory device in the memory may be a volatile memory device or a non-volatile memory device.

[0011] In the following description, a "persistent storage device" may refer to one or more persistent storage devices, which are an example of one or more storage devices. A persistent storage device may typically be a non-volatile storage device (e.g., an auxiliary storage device), and more specifically, may be, for example, a hard disk drive (HDD), a solid state drive (SSD), a non-volatile memory express (NVME) drive, or a storage class memory (SCM).

[0012] In the following description, the term "storage device" may refer to at least one of memory and persistent storage device.

[0013] Furthermore, in the following description, a "processor" may refer to one or more processor devices. The at least one processor device may typically be a microprocessor device such as a CPU (Central Processing Unit), but may also be another type of processor device such as a GPU (Graphics Processing Unit). The at least one processor device may be single-core or multi-core. The at least one processor device may also be a processor core. The at least one processor device may also be a processor device in a broader sense, such as a circuit that is a collection of gate arrays written in a hardware description language that performs some or all of the processing (for example, an FPGA (Field-Programmable Gate Array), a CPLD (Complex Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit)).

[0014] In the following description, functions are sometimes described using the expression "yyy unit." However, the functions may be realized by one or more computer programs executed by a processor, by one or more hardware circuits (e.g., FPGAs or ASICs), or by a combination thereof. When a function is realized by a program executed by a processor, the specified processing is performed using a storage device and / or an interface device, etc., as appropriate, and therefore the function may be considered to be at least a part of the processor. Processing described using a function as the subject may be processing performed by a processor or a device having the processor. A program may be installed from a program source. The program source may be, for example, a program distribution computer or a computer-readable storage medium (e.g., a non-transitory storage medium). The description of each function is merely an example; multiple functions may be combined into one function, or one function may be divided into multiple functions.

[0015] Hereinafter, the embodiments will be described with reference to the drawings.

[0016] FIG. 1 is a diagram showing an outline of the process from knowledge solicitation to royalty payment realized by a knowledge accumulation support system according to one embodiment of the present invention.

[0017] Here, "knowledge" is defined as "information in a specific field." An example of a "specific field" is a field specified in a job posting. "Knowledge" may include document entities such as files, or may include information as text entered into a specified input field.

[0018] The knowledge accumulation support system 3 (hereinafter sometimes referred to as "this system 3") owned by the knowledge manager 2 calls for knowledge from knowledge providers 1 with whom the knowledge manager 2 has a contractual relationship for information provision, and the knowledge providers 1 provide the knowledge (arrow 101). Here, knowledge providers 1 include not only individuals and companies that possess knowledge about operations in a specific field, but also BPO companies with experience in outsourcing businesses in various industries.

[0019] The collected knowledge is selected within this system 3 as to whether it is useful or not, and the selected knowledge (hereinafter referred to as "useful knowledge") and information about the knowledge provider 1 are stored within this system 3.

[0020] The useful knowledge is then converted into a template 5 (arrow 102) so that it can be used on a knowledge utilization platform 4 owned by a knowledge manager 2. Examples of the knowledge utilization platform 4 include an automatic checking tool for design drawings and a knowledge search tool.

[0021] The template 5 is sold to a sales destination 6 together with the knowledge utilization platform 4 (arrow 103), and sales information is recorded in the system 3 via a sales system or the like (arrow 104). The system 3 calculates a portion of the template sales as royalties according to the number of template 5 sold and the number of useful knowledge items that contributed to the creation of the template 5, and distributes this to the knowledge provider 1 (arrow 105).

[0022] The system 3 may be a physical computer system composed of one or more physical computers, and may include an interface device 1701, a storage device 1702, and a processor 1703 connected thereto, as illustrated in FIG. 17. The interface device 1701 communicates with external systems, such as the information processing terminal of the knowledge provider 1 (hereinafter referred to as the "provider terminal"), the information processing terminal of the knowledge manager 2 (hereinafter referred to as the "manager terminal"), the knowledge utilization platform 4, and the information processing terminal of the buyer 6 (hereinafter referred to as the "buyer terminal"). The storage device 1702 stores data and programs. The processor 1703 executes programs. The system 3 is not limited to a physical computer system, and may also be, for example, a logical computer system based on a physical computer system (e.g., a virtual machine or a cloud computing system). The "information processing terminal" referred to in this paragraph may be a computer such as a personal computer or a smartphone, or an input / output console such as an input device and a display device.

[0023] As examples of the present system 3, for example, the following examples 1 and 2 are conceivable. [Example]

[0024] FIG. 2 is a diagram showing an example of the configuration of the system 3 according to the first embodiment.

[0025] The knowledge accumulation support system 3 mainly has functions related to knowledge solicitation, knowledge reception, and royalty reception. Specifically, for example, by executing a program stored in the storage device 1702 on the processor, a knowledge solicitation-related function (input unit 21), a knowledge reception-related function (transmitting / receiving unit 31, similarity calculation unit 32, useful knowledge selection unit 33, and storage unit 34), and a royalty calculation-related function (provider management unit 41, classification rate calculation unit 42, sales reception unit 43, and royalty calculation unit 44) are realized.

[0026] The input unit 21 receives input of information such as a format for knowledge solicitation from the administrator terminal of the knowledge manager 2. Based on the input information, the transmitting / receiving unit 31 transmits solicitation information, which is information on the knowledge solicitation, to the provider terminal 201 of the knowledge provider 1. The knowledge provider 1 inputs knowledge into an input screen where the knowledge provider 1 inputs information in accordance with the solicitation information. The knowledge may include, for example, a document entity such as a file and an explanation for the document entity. Specific examples of each input screen will be described with reference to FIGS. 8 and 9.

[0027] The transmitter / receiver 31 receives knowledge input by the knowledge provider 1, and the similarity calculation unit 32 calculates the similarity with existing knowledge that has been previously input and stored by the knowledge manager 2. Here, "existing knowledge" refers to existing useful knowledge, and more specifically, to knowledge that has been determined to be useful knowledge by the system 3 and stored among the provided knowledge. One example of calculating the similarity with existing knowledge is a scoring method in which the existing knowledge and words in the knowledge are expressed as vectors, and the closeness between the vectors is calculated as cosine similarity.

[0028] The useful knowledge selection unit 33 identifies, from the provided knowledge, knowledge whose similarity to existing knowledge falls within an arbitrary threshold set in advance by the knowledge manager 2, and selects the identified knowledge as useful knowledge. The storage unit 34 stores the selected useful knowledge and provider information (information on the knowledge provider 1 of the knowledge selected as useful knowledge) in the storage device 1702. Here, the threshold for similarity can be determined by user input by the knowledge manager 2.

[0029] From this stored useful knowledge, templates 5 that can be used in the knowledge utilization platform 4 are created based on input received by the input unit 21. The provider management unit 41 tallies the number of useful knowledge items that contributed to template creation for each knowledge provider 1. Based on the tallied results, the distribution rate calculation unit 42 calculates the distribution rate for each knowledge provider 1 to which royalties will be paid. When a template 5 is sold, the sales receiving unit 43 separately receives sales information such as the number of template 5 sold and sales amount from the sales system 202 or the like. From the distribution rate calculated by the distribution rate calculation unit 42 and the sales information received by the sales receiving unit 43, the royalty calculation unit 44 calculates the royalties to be paid to each knowledge provider 1. The method of calculating the distribution rate and royalties will be explained with reference to FIG. 6.

[0030] Next, an example of the database configuration will be described with reference to FIG.

[0031] The database 341 is managed by the storage unit 34. A database 341 exists for each knowledge utilization platform 4. The databases 341 have a common configuration. The database 341 is stored in the storage device 1702 of the present system 3, but may also be stored in a storage device external to the present system 3.

[0032] Specifically, for example, database 341 is composed of fields such as knowledge provider name 342 in which data representing the name of knowledge provider 1 is stored, knowledge (before selection) 343 in which data as knowledge provided by knowledge provider 1 is stored, existing knowledge (explanation) 344 in which explanatory matters that have become existing knowledge regarding knowledge utilization platform 4 are stored, existing knowledge (document entity) 344 in which document entities (or links thereto) that have become existing knowledge regarding knowledge utilization platform 4 are stored, template 346 in which template 5 (or data that forms the basis of template 5) created regarding knowledge utilization platform 4 is stored, and distribution rate 347 in which data representing the distribution rate for each knowledge provider 1 calculated regarding knowledge utilization platform 4 is stored.

[0033] When knowledge is received in response to a solicitation, data indicating the name of the knowledge provider 1 who provided the knowledge is stored in knowledge provider name 342, and data as that knowledge is stored in knowledge (before selection) 343. The database 341 in which the data is stored is the database 341 corresponding to the knowledge utilization platform 4 related to that solicitation. The knowledge (data) stored in knowledge (before selection) 343 is stored temporarily, and the data is discarded after useful knowledge is selected.

[0034] If the knowledge stored in knowledge (before selection) 343 is determined to be useful knowledge, the explanation of the knowledge entered in the input form among the knowledge in knowledge (before selection) 343 is stored in existing knowledge (explanation field) 344, and the document entity is stored in existing knowledge (document entity) 344. These data are used to create templates, and are also used as similarity comparison targets for knowledge selection when new knowledge is solicited.

[0035] The created template 5 is stored in template 346, and the distribution rate calculated from the number of useful knowledge providers 1 used to create template 5 is stored in template 346. The distribution rate may be used each time sales information for template 5 is received.

[0036] Here, the types of knowledge will be organized with reference to Figure 4.

[0037] In this embodiment, there are three types of knowledge: knowledge 50, useful knowledge 51, and existing knowledge 52. After collecting knowledge 50, the system 3 calculates the similarity between the knowledge 50 and the existing knowledge 52 by comparing the similarity between the knowledge 50 and the existing knowledge 52 (S501). The system 3 determines whether the knowledge 50 is useful based on the calculated similarity, and selects the knowledge 50 if the determination result is that it is useful (S502). The selected knowledge is classified by the system 3 as useful knowledge 51. The system 3 uses the useful knowledge 51 to create a template 5, and also stores it as new existing knowledge 52 (S503).

[0038] Next, a series of flows will be described with reference to FIGS.

[0039] FIG. 5 is a flowchart of knowledge selection in this system 3.

[0040] The transmitting / receiving unit 31 transmits the knowledge solicitation information based on the input form (solicitation form) input to the input unit 21 (S60).

[0041] The transmitting / receiving unit 31 receives knowledge from the knowledge provider 1 via an input form (S61). The transmitting / receiving unit 31 reads the explanation portion of the knowledge from the received information based on the contents of the input form (S62). The storage unit 34 stores the knowledge in Knowledge (Before Selection) 343 in the database 341 corresponding to the knowledge utilization platform 4 related to the input form, stores data representing the name of the knowledge provider 1 in Knowledge Provider Name 342, and refers to all existing knowledge in the database 341 (Existing Knowledge (Explanation) 344 and Existing Knowledge (Document Entity) 345). The similarity calculation unit 32 calculates the similarity of the received knowledge with all existing knowledge (S63). The unit of similarity may be, for example, %, and a similarity of "100%" may mean that the knowledge is identical to the existing knowledge. Furthermore, when there are multiple existing knowledges, the similarity of knowledge to the existing knowledges may be a statistical value of the similarity of the multiple existing knowledges (for example, the maximum or average value of the similarity).

[0042] Thereafter, the useful knowledge selection unit 33 determines whether the calculated similarity is within a specific threshold range (x% or more and y% or less) (S64). Note that the upper limit y% of the threshold range of similarity may be 100%.

[0043] If the judgment result of S64 is true (S64: Yes), the useful knowledge selection unit 33 classifies the received knowledge as useful knowledge (S65) and stores the received knowledge in the existing knowledge (explanation) 344 and / or existing knowledge (document entity) 345 of the database 64.

[0044] If the determination result in S64 is false (S64: No), the useful knowledge selection unit 33 discards the received knowledge from the knowledge (before selection) 343 in the database 341.

[0045] Steps S63 to S66 are performed for each piece of knowledge that is read. As a result, knowledge selection is performed and judged for each piece of knowledge, and useful knowledge is stored (updated) as existing knowledge, so that it can be used for the next useful knowledge judgment.

[0046] FIG. 6 is a flowchart of the template creation process of the system 3.

[0047] The storage unit 34 determines whether the conditions for creating or updating a template are met (S70). An example of the condition may be that a certain number n or more of useful knowledge has been collected in the knowledge selection (n may be any natural number). Instead of or in addition to the fact that n or more useful knowledge has been collected, the condition may be that the current time is within a certain time period. The start time of the "specified time period" may be the time when the recruitment began, or the time when the first knowledge or useful knowledge is accumulated for the recruitment. The end time of the "specified time period" may be the time when a certain amount of time has elapsed since the start time, or the end time of the day to which the start time belongs (for example, 24:00).

[0048] If the determination result of S70 is false (S70: No), this flow ends. The determination of whether a certain number or more of useful knowledge has been collected may be made by determining whether the total number of existing knowledge stored as useful knowledge is a certain number or more.

[0049] If the determination result in S70 is true (S70: Yes), a template 5 is created or updated from the data stored in the existing knowledge (explanatory items) 344 and the existing knowledge (document entity) 345 (S71), and the storage unit 34 saves the created or updated template 5 in the template 346 of the database 341 (S72). Note that this creation or update is performed by the template creation unit 90 in the second embodiment described below, but in this embodiment it may be performed by the knowledge manager 2.

[0050] Thereafter, the distribution rate calculation unit 42 calculates or updates the distribution rate for the created or updated template 5 from the number of useful knowledge items (number of existing knowledge items) (S73), and stores the calculated or updated distribution rate in the distribution rate 347 of the database 341.

[0051] Here, for each knowledge provider 1, the "distribution rate" is the value obtained by dividing the number of useful knowledge items provided by that knowledge provider 1 by the total number of useful knowledge items that make up template 5. For example, if the number of useful knowledge items provided by knowledge provider 1 is 3 and the total number of useful knowledge items that make up template 5 is 100, the distribution rate is 3%. If there are multiple templates 5 for one knowledge utilization platform 4, and the total number of useful knowledge items provided by knowledge providers 1 for those multiple templates 5 is 3 and the total number of useful knowledge items that make up those multiple templates 5 is 100, the distribution rate is also 3%.

[0052] FIG. 7 is a flowchart of royalty calculation in the present system 3.

[0053] The sales receiving unit 43 receives sales information for each created template (S80), and a percentage of the sales represented by the sales information (for example, a percentage designated in advance by the knowledge manager 2) is used as the total royalty. The total sales represented by the sales information for all templates 5 may serve as the base for the total royalty. The royalty calculation unit 44 multiplies the total royalty by the distribution rate represented by distribution rate 347, and calculates the royalty to be paid to the knowledge provider 1 (S81). For example, if the sales of template 5 are 1 million yen, of which 30% is royalty, and the distribution rate for a certain knowledge provider 1 is 3%, the royalty to be paid to that knowledge provider 1 will be 9,000 yen (= 1 million yen × 30% × 3%).

[0054] The type of template to be created is not limited to one, and multiple types may be created. In this embodiment, examples of two types of templates will be described with reference to Figures 8 to 13. Specifically, with reference to Figures 8 to 10, an example will be described in which the knowledge utilization platform 4 is an automatic design drawing check tool, and with reference to Figures 11 to 13, an example will be described in which the knowledge utilization platform 4 is a knowledge search tool.

[0055] FIG. 8 shows an example of a knowledge recruitment screen.

[0056] In the example of Figure 8, the knowledge utilization platform 4 is assumed to be an automatic design drawing checking tool that automatically checks CAD design drawings, and the created template is assumed to be a program. The knowledge solicitation screen 800 is a user interface (typically a graphical user interface) for the knowledge manager 2, and has input fields 801 to 805. The knowledge manager 2 enters the purpose of the solicitation as the use of the knowledge specification in input fields 801 and 802, and enters examples of the knowledge they want in input field 803. According to the example of Figure 8, documents describing design defect cases and processing constraint conditions are solicited as knowledge in order to create a check program based on processing rules.

[0057] In the description field, columns are specified to provide an item-by-item overview of the knowledge to be provided. In the example of Figure 8, in order to clearly indicate which parts of the design drawing the check program is measuring the distance between, there are columns for Measurement Target 1, which represents the part to be compared, Measurement Target 2, which represents the part to be compared, a threshold for the measured distance (the distance between those parts), and Reference Material 1 and Reference Material 2, for registering document entities (for example, actual drawings) as reference materials, and descriptions of these columns are entered in input field 804. In the other recruitment conditions, detailed knowledge requirements can be entered in free format in input field 805.

[0058] Recruitment information based on the information entered on this recruitment screen 800 is, for example, posted on a website or sent by email to each knowledge provider 1 (for example, a member who has registered as a user beforehand).

[0059] FIG. 9 shows an example of a screen for the knowledge provider 1 to input knowledge in response to a recruitment based on the recruitment screen 800 shown in FIG.

[0060] The input screen 900 is a user interface (typically a graphical user interface) for the knowledge provider 1, and has input fields 901 to 906. In the example of FIG. 9, the knowledge provider 1 is assumed to be an employee of a company. The knowledge provider 1 enters information about the provider, contact details, etc. in the input fields 901 to 905. The information entered in the input fields 901 to 905 is managed, for example, by the provider management unit 41.

[0061] 8 has an input field 906 with columns 911 to 915 corresponding to the columns shown in the example. The knowledge provider 1 enters appropriate items in each of columns 911 to 915 and stores them together with the document entity as knowledge. Uploads of document entities from the knowledge provider 1 are accepted through columns 914 and 915.

[0062] The storage unit 34 counts each line in this input field 906 (explanation field) as one piece of knowledge. The similarity with existing knowledge is calculated for each piece of knowledge. If the calculated similarity is within a threshold range, the knowledge is identical to or similar to the existing knowledge (useful knowledge provided in the past). If the calculated similarity is outside the threshold range, for example, the knowledge is irrelevant to the scope of the current recruitment.

[0063] Figure 10 shows an example of a template created based on existing knowledge about automatic design drawing checking tools.

[0064] In the example of Figure 10, templates 5A, 5B, ... of the individual programs in set 1000 of check rule programs for each processing requirement correspond to template 5. When creating a new template 5, it is assumed that a rule set for a new processing requirement is added, and when updating template 5, it is assumed that rules within the rule set are added or brushed up. These template 5 sets 1000 are sold as a set with a check tool, which is platform 4, and a portion of the sales of template set 1000 is paid back to knowledge provider 1 as royalties.

[0065] FIG. 11 shows an example of a knowledge solicitation screen when creating a template for a knowledge search tool.

[0066] The template for the knowledge search tool is assumed to be document-based. In the example of Fig. 11, knowledge about work-related accidents at manufacturing sites is sought. The basic configuration of the knowledge request screen 1100 is the same as the configuration of the screen 800 shown in Fig. 8, but the information entered in the description field corresponds to attribute information in the knowledge search and is expected to assist the knowledge search.

[0067] FIG. 12 shows an example of a screen for the knowledge provider 1 to input knowledge to the recruitment screen 1100 shown in FIG.

[0068] The configuration of this screen 1200 is essentially the same as the configuration of the screen 900 illustrated in Fig. 9. For each document related to a disaster case, the knowledge provider 1 writes an explanation of the disaster case in columns 1211 to 1216 corresponding to the columns specified on the recruitment screen 1100. As in Fig. 9, one line in the explanation column 1206 is counted as one piece of knowledge.

[0069] FIG. 13 shows an example of a template created based on existing knowledge for a knowledge search tool.

[0070] In the example of a knowledge search tool, a table of specialized examples for each use case of the knowledge search tool corresponds to Template 5, and the set of tables (templates) 5P to 5Q corresponds to Database 1300. Specific use case examples include referencing past accident information as a safety measure at the site, and referencing past examples of poor design to supplement the perspective of a design review to improve design quality. For each use case, items in the description column of knowledge that has been provided and deemed useful are accumulated as Database 1300, and Database 1300 is sold as a template set together with the search tool.

[0071] In this way, there is this system 3 that links knowledge providers 1 with knowledge managers 2. This system 3 makes it possible to collect knowledge from multiple knowledge providers 1, even for knowledge that is difficult for individuals to collect, by providing a mechanism that provides an incentive called royalty. In addition, knowledge can be collected in a form that matches the knowledge utilization platform 4, and by creating a template 5, it is possible to accumulate and provide knowledge in a more practical manner. [Example]

[0072] The second embodiment will be described below, focusing mainly on the differences from the first embodiment, and explanations of the commonalities with the first embodiment will be omitted or simplified.

[0073] In the first embodiment, the template 5 is created based on the input of the knowledge manager 2, but in the second embodiment, the template 5 is created automatically.

[0074] FIG. 14 is a diagram illustrating an example of the configuration of the system 3 according to the second embodiment.

[0075] 2, the system 3 has a template creation unit 90. The template creation unit 90 automatically creates (or automatically updates) a template 5 from useful knowledge in accordance with the purpose of the recruitment, and stores the created (or updated) template 5 in a database 341 provided for each knowledge utilization platform 4.

[0076] FIG. 15 is a flowchart showing the automatic creation of template 5 for the design drawing automatic check tool.

[0077] The flow shown in Figure 15 is a detailed example of "Create and update templates from useful knowledge" (S71) in the flowchart in Figure 6. Here, it is assumed that a generation AI will be used to automatically create check programs.

[0078] First, the template creation unit 90 acquires the content of the input field (explanation field) 906 of useful knowledge (S91), generates a prompt to instruct the generation AI based on that content, and outputs the generated prompt to the generation AI (S92). For example, for the first line of the input field 906 in Figure 9, the prompt generated and output based on the information entered in columns 911 to 913 is "Please create a program that determines that a violation occurs when the distance between holes is 10 mm or less." The template creation unit 90 instructs the generation AI to generate a prompt for each piece of knowledge, and template 5 is created (S93).

[0079] FIG. 16 is a flowchart of the automatic creation of a template 5 for a knowledge search tool.

[0080] Because the template created is document-based, it can be created based on the contents of the input field (explanation field) 1206 that has been determined to be useful knowledge. Like FIG. 15, the flow shown in FIG. 16 is a detailed example of "Creating / updating a template from useful knowledge" (S71) in the flowchart of FIG. 6. The template creation unit 90 first acquires the contents of the explanation field 1206 of the useful knowledge (S101), then aggregates the contents based on the acquired contents and outputs the aggregated contents as a file (S102). The output file is the search target data in the knowledge search tool, and becomes template 5.

[0081] In this way, there is a system 3 that converts knowledge collected from knowledge providers 1 into templates in an integrated manner. This system 3 accelerates the process from knowledge collection to template sales, making it possible to collect knowledge from knowledge providers 1 more efficiently.

[0082] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those including all of the described configurations. Furthermore, part of the configuration of one embodiment can be replaced with the configuration of another embodiment, or the configuration of another embodiment can be added to the configuration of one embodiment. Furthermore, part of the configuration of each embodiment can be added, deleted, or replaced with other configurations. Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be implemented in hardware, in part or in whole, by designing, for example, an integrated circuit. Furthermore, the above-described configurations, functions, etc. may be implemented in software, by a processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files that realize each function can be stored in memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0083] In addition, a mobile phone network compliant with the so-called 5G standard can also be applied to the communication network for communication within this system 3 and / or the communication network for communication between this system 3 and the outside of this system 3.

[0084] The above description can be summarized as follows: The following summary may include supplementary explanations and explanations of variations of the above description.

[0085] The knowledge accumulation support system (e.g., this system 3) has a knowledge reception-related unit (an example of a first function) and a royalty calculation-related unit (an example of a second function). The knowledge reception-related unit includes, for example, at least a portion of a transmission / reception unit 31, a similarity calculation unit 32, a useful knowledge selection unit 33, and a storage unit 34. The royalty calculation-related unit includes at least a portion of a knowledge provider management unit 41, a distribution rate calculation unit 42, a sales reception unit 43, and a royalty calculation unit 44.

[0086] The knowledge reception-related unit receives knowledge from a knowledge provider in response to one of one or more solicitations corresponding to one or more knowledge utilization platforms, and stores the received knowledge in a storage device (e.g., storage device 1702). The storage device may be located inside or outside the knowledge storage support system. The knowledge reception-related unit calculates the similarity of the received knowledge with one or more useful knowledge items stored in the storage device, and determines whether the received knowledge is useful knowledge based on the calculated similarity. If the received knowledge is determined to be useful knowledge, the knowledge reception-related unit adds the knowledge to the storage device as useful knowledge.

[0087] The royalty calculation related unit calculates royalties to each knowledge provider who provided knowledge in response to one or more solicitations corresponding to one or more knowledge utilization platforms, based on the number of pieces of knowledge provided by the knowledge provider that were deemed useful knowledge, and outputs data for payment of the royalties.

[0088] This increases the incentives for knowledge providers, thereby promoting the accumulation of knowledge.

[0089] It should be noted that "knowledge" may be information (for example, information about know-how or experience) held by a knowledge provider (for example, a company or its employees).

[0090] Furthermore, each of the "one or more knowledge utilization platforms" is a system, which may be hardware, software (e.g., an application or middleware), or a combination thereof. The knowledge utilization platform may be, for example, a system that serves as a foundation for utilizing useful knowledge entered in response to one or more recruitments corresponding to the knowledge utilization platform as digital products (e.g., templates, described below).

[0091] Furthermore, each of the "one or more useful knowledge stored in the storage device" is knowledge that was previously entered in response to a call for proposals corresponding to the accepted knowledge and selected as useful knowledge. An example of useful knowledge stored in the storage device is the "existing knowledge" in the first and second embodiments.

[0092] Furthermore, the "similarity" may be calculated using a known similarity calculation method, for example, the similarity may be calculated from the result of comparing the vector of a word in knowledge with the vector of a word in useful knowledge.

[0093] The royalty calculation unit may calculate, for each of one or more knowledge utilization platforms, a distribution rate for each knowledge provider who provided knowledge in response to one or more solicitations corresponding to that knowledge utilization platform, based on the total number of useful knowledge pieces stored in the storage device for that knowledge utilization platform and the number of pieces of knowledge provided by that knowledge provider that were determined to be useful knowledge, and may calculate royalties for that knowledge provider based on that distribution rate and sales results of services related to that knowledge utilization platform. The distribution rate corresponds to the contribution rate of the knowledge provided by that knowledge provider for each knowledge provider, and therefore royalties according to the contribution rate can be returned to the knowledge provider, thereby increasing the incentives of the knowledge provider.

[0094] The "services related to the knowledge utilization platform" being sold may include the knowledge utilization platform itself, may include the templates described below that are created for the knowledge utilization platform, or may include both the knowledge utilization platform and the templates.

[0095] The "sales result" may be a base amount for royalties, such as the sales amount of the product, the profit based on the sales, or the actual number of purchases of the product. Data representing the sales result may be input to the knowledge accumulation support system from an external system such as the sales system 202.

[0096] When the distribution rate is calculated on a knowledge utilization platform basis, the "total number of accumulated useful knowledge pieces" may be the total number of useful knowledge pieces provided and accumulated for that knowledge utilization platform. When the distribution rate is calculated on a template basis, the "total number of accumulated useful knowledge pieces" may be the total number of useful knowledge pieces provided and accumulated in response to recruitment.

[0097] For each knowledge provider, the "distribution rate" may be the ratio of the number of pieces of knowledge provided by that knowledge provider to the total number of pieces of useful knowledge, or may be a value that reflects some weighting on that ratio.

[0098] For each of one or more knowledge utilization platforms, a template for utilizing the knowledge utilization platform may be created for each of one or more solicitations corresponding to the knowledge utilization platform, based on useful knowledge stored in a storage device related to the solicitation. A "template" may be data (e.g., an option such as an accessory to the knowledge utilization platform) formed from useful knowledge for a commercial product, and specifically may be, for example, a program or document. Based on the sales results of services including one or more templates created for the knowledge utilization platform, royalties to each knowledge provider who provided knowledge for one or more solicitations corresponding to the knowledge utilization platform may be calculated. As a result, since useful knowledge is used to create templates, sales promotion of sales targets including templates is expected, which is expected to increase royalties and, as a result, promote the provision of knowledge.

[0099] For each of one or more knowledge utilization platforms, the royalty calculation-related unit may calculate or update the distribution rate when a template is created or updated for that knowledge utilization platform. This allows the distribution rate to be calculated at an appropriate time, which is expected to reduce the calculation load on the knowledge accumulation support system.

[0100] The knowledge accumulation support system may further include an automatic template creation related unit (an example of a third function). The automatic template creation related unit may include, for example, a template creation unit 90. For at least one of the one or more knowledge utilization platforms, the automatic template creation related unit may create a template for utilizing the knowledge utilization platform for each of one or more solicitations corresponding to the knowledge utilization platform, based on useful knowledge stored in a storage device related to the solicitation. This is expected to enable efficient creation of templates based on useful knowledge, thereby improving the efficiency of the process leading up to the sale of sales items including templates. As a result, it is expected to speed up the return of royalties, thereby promoting the provision of knowledge.

[0101] For each of one or more solicitations corresponding to at least one knowledge utilization platform, the solicitation may be a solicitation for information on each of a specified plurality of knowledge items. Knowledge received in response to the solicitation may include information input by a knowledge provider for each of the plurality of knowledge items. The automatic template creation related unit may create or update a template corresponding to the solicitation based on the information input for each of the plurality of knowledge items for the solicitation. This is expected to result in efficient template creation. Note that the "plurality of knowledge items" may correspond to, for example, the column names of the plurality of columns 911-915 in the input field (description field) 906 or the column names of the plurality of columns 1211-1216 in the input field (description field) 1206. The knowledge may include text entered in a column or a document (e.g., a file) uploaded via a column.

[0102] For at least one of the one or more job postings corresponding to at least one knowledge utilization platform, the multiple knowledge items may include knowledge items corresponding to elements and thresholds related to the elements. The automatic template creation unit may include, in the template corresponding to the job posting, statistical values ​​(e.g., maximum, minimum, or average) of one or more thresholds entered for each element represented by information entered by one or more knowledge providers as thresholds for the element. This is expected to enable efficient creation of appropriate templates. For example, the template may be a program, and each check performed by the program may be compared with a threshold, and the threshold corresponding to the check may be determined based on statistical values ​​of thresholds held by one or more useful knowledge for that check. Specifically, for example, in Template 5A illustrated in FIG. 10, for each of checks #1 to #3, the threshold to be compared in that check may be determined based on statistical values ​​of thresholds held by one or more useful knowledge for that check.

[0103] For each of one or more knowledge utilization platforms, for each of one or more solicitations corresponding to that knowledge utilization platform, a knowledge input screen (e.g., a GUI (Graphical User Interface)) for that solicitation may have a UI component (e.g., a GUI component) that accepts input of information for each of a plurality of knowledge items defined for that solicitation. As a result, since at least a portion of the knowledge configuration is defined, knowledge providers only need to input knowledge according to that defined configuration, which makes it easier to input knowledge and is expected to promote knowledge provision.

[0104] A template may be created or updated when the number of accumulated useful knowledge pieces for at least one of the one or more recruitments is equal to or greater than a predetermined threshold. This allows the template to be created or updated at an appropriate time, thereby reducing the computational load of the knowledge accumulation support system. For example, the knowledge reception-related unit may monitor whether the number of accumulated useful knowledge pieces is equal to or greater than a predetermined threshold. When the number of accumulated useful knowledge pieces is less than the predetermined threshold, the knowledge reception-related unit may prohibit manual or automatic template creation-related unit from creating or updating a template. When the number of accumulated useful knowledge pieces is equal to or greater than the predetermined threshold, the knowledge reception-related unit may allow manual or automatic template creation-related unit to create or update a template. Such monitoring may be performed by the automatic template creation-related unit instead of or in addition to the knowledge reception-related unit. The automatic template creation-related unit may create or update a template when the number of accumulated useful knowledge pieces is equal to or greater than a predetermined threshold.

[0105] For at least one of the one or more recruitments, a template may be created or updated if the current time is within a predetermined time period. This prevents templates from being created or updated outside of the predetermined time period, which is expected to reduce the computational load of the knowledge accumulation support system. For example, the knowledge reception-related unit may monitor whether the current time is within a predetermined time period (and, for example, whether the number of useful knowledge items is equal to or greater than a predetermined threshold). If the monitoring result is false, the knowledge reception-related unit may prohibit manual or automatic template creation-related unit from creating or updating a template. If the monitoring result is true, the knowledge reception-related unit may allow manual or automatic template creation-related unit to create or update a template. Such monitoring may be performed by the automatic template creation-related unit instead of or in addition to the knowledge reception-related unit. The automatic template creation-related unit may create or update a template if the monitoring result is true.

[0106] If the received knowledge is not determined to be useful knowledge, the knowledge reception unit may delete the knowledge from the storage device, thereby reducing the increase in storage capacity consumption.

[0107] One or more templates may be created for one knowledge utilization platform, and one or more knowledge requests may exist for one knowledge utilization platform. [Explanation of symbols]

[0108] 3...knowledge accumulation support system, 21...input unit, 31...transmitting / receiving unit, 32...similarity calculation unit, 33...useful knowledge selection unit, 34...storage unit, 346...template, 41...knowledge provider management unit, 42...distribution rate calculation unit, 43...sales receiving unit, 44...royalty calculation unit

Claims

1. The system includes a knowledge reception section and a royalty calculation section, The knowledge reception related unit Accepting knowledge from a knowledge provider in response to one of one or more solicitations corresponding to one or more knowledge utilization platforms, each of which is a system; The accepted knowledge is stored in a storage device, Calculating the similarity of the received knowledge with useful knowledge previously input in response to a solicitation corresponding to the knowledge and one or more pieces of selected useful knowledge stored in the storage device; Based on the calculated similarity, it is determined whether the accepted knowledge is useful knowledge or not; If the received knowledge is determined to be useful knowledge, add the knowledge to the storage device as useful knowledge; The royalty calculation related unit For each of the one or more knowledge utilization platforms, calculate royalties to each knowledge provider who provided knowledge in response to one or more solicitations corresponding to the knowledge utilization platform, based on the number of pieces of knowledge provided by the knowledge provider that were determined to be useful knowledge, and output data for payment of the royalties; Knowledge accumulation support system.

2. The royalty calculation related unit For each of the one or more knowledge utilization platforms, for each knowledge provider who provided knowledge in response to one or more solicitations corresponding to the knowledge utilization platform, calculate a distribution rate based on the total number of useful knowledges stored in the storage device for the knowledge utilization platform and the ratio of the number of knowledges provided by the knowledge provider that were determined to be useful knowledge, and calculate royalties to the knowledge provider based on the distribution rate and sales results of services related to the knowledge utilization platform; 2. The knowledge accumulation support system according to claim 1.

3. For each of the one or more knowledge leveraging platforms: For each of one or more recruitments corresponding to the knowledge utilization platform, a template for utilizing the knowledge utilization platform is created based on useful knowledge related to the recruitment stored in the storage device; Based on the sales results of services including one or more templates created for the knowledge utilization platform, royalties are calculated for each knowledge provider who provides knowledge in response to one or more solicitations corresponding to the knowledge utilization platform.

2. The knowledge accumulation support system according to claim 1.

4. For each of the one or more knowledge utilization platforms, the royalty calculation-related unit: For each knowledge provider who has provided knowledge in response to one or more solicitations corresponding to the knowledge utilization platform, a distribution rate is calculated or updated when the template is created or updated for the knowledge utilization platform, the distribution rate being the ratio of the number of pieces of knowledge provided by the knowledge provider and deemed useful knowledge to the total number of pieces of useful knowledge stored in the storage device for the knowledge utilization platform; Calculate royalties to each knowledge provider based on the distribution rate at the time of sales of services related to the knowledge utilization platform and the results of the sales; 4. The knowledge accumulation support system according to claim 3.

5. Further, the apparatus includes an automatic template creation section, For at least one knowledge utilization platform among the one or more knowledge utilization platforms, the automatic template creation related unit: For each of one or more recruitments corresponding to the knowledge utilization platform, create the template for utilizing the knowledge utilization platform based on useful knowledge related to the recruitment stored in the storage device; 4. The knowledge accumulation support system according to claim 3.

6. For each of the one or more job postings corresponding to the at least one knowledge utilization platform, the request is for information about each of a plurality of specified knowledge items; The knowledge received in response to the solicitation includes information input by a knowledge provider for each of the plurality of knowledge items; the automatic template creation related unit creates or updates the template corresponding to the recruitment based on information input for each of the plurality of knowledge items regarding the recruitment; 6. The knowledge accumulation support system according to claim 5.

7. For at least one of the one or more recruitments corresponding to the at least one knowledge utilization platform, the plurality of knowledge items include a knowledge item corresponding to an element and a knowledge item corresponding to a threshold value related to the element; the automatic template creation related unit includes, in the template corresponding to the recruitment, statistical values ​​of one or more input thresholds for each element represented by information input from one or more knowledge providers, as thresholds for the element; 7. The knowledge accumulation support system according to claim 6.

8. For each of the one or more knowledge leveraging platforms: For each of one or more recruitments corresponding to the knowledge utilization platform, a knowledge input screen for the recruitment has a UI component that accepts input of information for each of a plurality of knowledge items defined for the recruitment; 2. The knowledge accumulation support system according to claim 1.

9. creating or updating the template when the number of accumulated useful knowledge for at least one of the one or more recruitments is equal to or greater than a predetermined threshold; 2. The knowledge accumulation support system according to claim 1.

10. For at least one of the one or more recruitments, if the current time is within a predetermined time, the template is created or updated.

2. The knowledge accumulation support system according to claim 1.

11. the knowledge reception unit deletes the received knowledge from the storage device if the received knowledge is not determined to be useful knowledge; 2. The knowledge accumulation support system according to claim 1.

12. Accepting knowledge from a knowledge provider in response to one of one or more solicitations corresponding to one or more knowledge utilization platforms, each of which is a system; The accepted knowledge is stored in a storage device, Calculating the similarity of the received knowledge with useful knowledge previously input in response to a solicitation corresponding to the knowledge and one or more pieces of selected useful knowledge stored in the storage device; Based on the calculated similarity, it is determined whether the accepted knowledge is useful knowledge or not; If the received knowledge is determined to be useful knowledge, add the knowledge to the storage device as useful knowledge; For each of the one or more knowledge utilization platforms, calculate royalties to each knowledge provider who provided knowledge in response to one or more solicitations corresponding to the knowledge utilization platform, based on the number of pieces of knowledge provided by the knowledge provider that were determined to be useful knowledge, and output data for payment of the royalties; A knowledge accumulation support method that uses a computer.

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