Matching support system and matching support method

Abstract

To provide a matching support system and a matching support method for supporting suitable matching between clients and service providers.SOLUTION: A matching support system stores basic information that is information related to each of a plurality of providers of a service, request information that is information related to a request received from a client of the service, a reliability level that is information indicating a level of reliability of each of the plurality of providers, and information indicating an expertise level of each of the providers in relation to the service. The matching support system determines a difficulty level of the request on the basis of the request information, generates first extraction results by extracting candidate providers of the service from the basic information so as to extract providers having higher reliability levels as the difficulty level of the request becomes higher, generates second extraction results by extracting candidate providers of the service from the first extraction results so as to extract providers having higher expertise levels in relation to the service as the difficulty level of the request becomes higher, and presents a user with the candidate providers based on the second extraction results.SELECTED DRAWING: Figure 8

Description

Technical Field

[0001] The present invention relates to a matching support system and a matching support method.

Background Art

[0002] Conventionally, various mechanisms have been proposed for assisting in the matching between a requester (service recipient) and a service provider when the requester requests the provision of a service.

[0003] For example, Patent Document 1 describes an educational mediation processing device that pre-evaluates the level of a teacher and introduces a teacher suitable for the level of a student to the student. The educational mediation processing device evaluates the level of teachers recruited by teacher recruitment means, and mediates between teachers and students with an evaluation level corresponding to the level of students recruited by student recruitment means. Further, the educational mediation processing device conducts a predetermined test on a teacher and evaluates the level of the teacher according to the test results. Further, the educational mediation processing device extracts teachers with an evaluation level corresponding to the level of the obtained students, and allows the student to select a desired teacher from the extracted teachers.

[0004] Select suitable supporter candidates from multiple approved supporters included in the support registration data. Select. The support system will also select from multiple approved supporters included in the support registration data. Priority will be given to selecting supporter candidates who meet the individual trust level set by the administrator. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2002-183487 [Patent Document 2] Japanese Patent Publication No. 2020-170424 [Overview of the project] [Problems that the invention aims to solve]

[0006] When a client makes a request to a service provider, the client may, for example, say, "The service is appropriate..." "I want to choose a contractor who will diligently carry out the work," "I want a contractor who will handle it at a fair price." "I would like to request a service," "I would like to request a service from an agency that is well-versed in the field of the service I would like to request." The outsourcing company will be selected based on the following criteria. On the other hand, the service provider will be selected based on operational efficiency and workload. From a leadership and education perspective, "If you have little experience (have not built trust), various services..." I have extensive experience in services that do not require a high level of specialization (services where specialization is not necessarily required) in this field. By doing so, I want to assess my own expertise and increase my credibility as a service provider," If you have extensive experience, you can further enhance your expertise by focusing on highly specialized services. "I want to gradually increase my credibility as a service provider." Matching between service providers and clients is not only about the client's perspective, but also about the service provider's perspective. It is desirable to consider the perspective of the provider as well.

[0007] In the above-mentioned Patent Document 1, the teacher's level is evaluated in advance, and a teacher is assigned to match the student's level. Introduce this to the students. Also, in the above Patent Document 2, the user can determine the experience level of the supporter candidate and their Based on other information (such as qualifications), reliable supporter candidates will be selected. However, in any case Regarding the mechanisms described in the literature, we also consider the perspective of the client and the intentions of the service provider. Based on this, matching between the client (student, user) and the service provider (teacher, potential supporter) This is not intended to be a game.

[0008] This invention supports appropriate matching between clients (service recipients) and service providers. To provide a matching support system and matching support method that enable this The objective. [Means for solving the problem]

[0009] One of the present inventions for achieving the above objectives is to enable the service provider to enable the client A service that facilitates matching between clients and service providers when requesting services. A checking support system, comprising an information processing device having a processor and a memory device. Basic information, which is information about each of the multiple aforementioned providers, received from the aforementioned requester. Request information, which is information related to the request, and information indicating the degree of trustworthiness of each of the aforementioned providers. The reliability level and information indicating the expertise of each provider in the aforementioned services are described. A difficulty determination unit that remembers and determines the difficulty level of the request based on the request information, and the difficulty level The provision of the service such that the higher the level of the request, the more reliable the provider is selected. Extract candidates from the basic information and generate a first extraction result that describes the extracted result. The first extraction unit, and the higher the difficulty of the request, the higher the professionalism of the service provider is extracted. Extract candidates for service providers from the first extraction result so that a second extraction unit that generates a second extraction result that describes the extracted result.

[0010] In addition, the problems disclosed in the present application and the solutions thereto are described in the section for the mode of implementing the invention and the drawings.

Effect of the Invention

[0011] According to the present invention, appropriate matching between the requester (service user) and the service provider can be supported.

Brief Description of the Drawings

[0012] [Figure 1] It is an example of a matching support system. [Figure 2] It is an example of the functions provided by the proxy request support device of the first embodiment. [Figure 3] It is an example of a reliability determination table. [Figure 4] It is an example of a specialized field determination table. [Figure 5] It is an example of a basic information table. [Figure 6] It is an example of a proxy history table. [Figure 7] It is an example of a request status table. [Figure 8] It is a flowchart for explaining the proxy request support process of the first embodiment. [Figure 9] It is a flowchart for explaining an example of the first extraction process. [Figure 10] It is a flowchart for explaining an example of the second extraction process. [Figure 11]This is a flowchart illustrating an example of the process for generating a confidence level determination table. [Figure 12A] This is an example of a table showing the correspondence between the number of applications and the points awarded. [Figure 12B] This is an example of a table showing the correspondence between acceptance rates and scores. [Figure 12C] This is an example of a correspondence table between the average value and score of client evaluations. [Figure 13] This flowchart illustrates an example of the process for generating a specialized field determination table. [Figure 14A] This is an example of a screen for selecting a specialty. [Figure 14B] This is an example of a screen for confirming competency information. [Figure 15] This is an example of a request evaluation submission screen. [Figure 16] This is an example of an information processing device used in the configuration of a matching support system. [Figure 17] This is an example of the functions provided by the proxy request support device of the second embodiment. [Figure 18A] This diagram shows how the difficulty determination unit generates the difficulty determination result. [Figure 18B] This diagram shows how the workload determination unit generates the workload determination result. [Figure 19] This is an example of a work schedule request screen. [Figure 20] This is an example of a workload determination table. [Figure 21] This is a flowchart illustrating the proxy request support process in the second embodiment. [Figure 22] This is a flowchart explaining the third extraction process. [Figure 23] This diagram illustrates the general outline of the third extraction result generation process. [Figure 24] This is a flowchart explaining the third extraction result generation process. [Figure 25] This is a flowchart explaining the fourth extraction result generation process. [Figure 26] This is an example of the functions provided by the proxy request support device of the third embodiment. [Figure 27]This is an example of a screen for receiving requests for a specific client level. [Figure 28] This is an example of a basic information table. [Figure 29] This is an example of a client evaluation table. [Modes for carrying out the invention]

[0013] Embodiments of the present invention will be described below with reference to the drawings. The images are illustrative examples for illustrating the present invention, and may be omitted or simplified as appropriate for clarity of explanation. This has been done. The present invention can also be implemented in various other forms.

[0014] In the following explanation, when describing identification information, the terms "identifier," "name," and "ID" will be used. While expressions such as "number" are used, these can be substituted for each other. Furthermore, in the following explanation, various types of information will be described using expressions such as "table" and "information". However, various types of information may be represented using data structures other than these. To indicate that it is independent of the table structure, "XX table," etc., may be referred to as "XX information." Yes. Also, in the following explanation, "database" will be written as "DB". Yes. Also, in the following explanation, redundant explanations of the same or similar configurations have been omitted. This may happen. Also, in the following explanation, the letter "S" preceding the symbol indicates a processing stage. It means "up".

[0015] [First Embodiment] The following is an information processing system according to one embodiment of the present invention (hereinafter referred to as "matching support system") This will be explained. Matching support system 1 is a system that allows clients to use services. Requesting the provision of services from a person who provides such services (hereinafter referred to as the "service provider") It assists in matching clients and service providers during the process. The clients and service providers targeted by Tem 1 are not necessarily limited. In the following, the clients However, these are individuals or companies, and the service providers are subject to various actions taken by the national government, local government, and other organizations. A person who provides services to handle the processing of applications on behalf of others (for example, a service provider that is a lawyer or judicial officer) This explanation will use the example of legal professionals such as legal scriveners and administrative scriveners (hereinafter referred to as "agency providers"). I will reveal it.

[0016] When a client requests a service provider to perform a service, for example, they might say, "The service will be performed appropriately." "I want to choose a service provider that will do the job for me," "I want to entrust the job to a service provider that will handle it at a reasonable price." "I want to entrust the request to an agency that is well-versed in the field of the service I want to request." We will select an outsourcing company from this perspective. On the other hand, we will select outsourcing companies that are "inexperienced (low reliability)". Service providers may not have a high level of expertise in various service areas (expertise is not necessarily required). By gaining broad experience in services (even those not requested), employees can assess their own expertise while providing services. "We want to increase trust as a provider," "We want experienced individuals to provide highly specialized services." By focusing on this, you can further enhance your expertise and build trust as a service provider. There is a desire to improve this. Matching support system 1 is designed to meet these requests. Taking into account the perspectives of both the client and the service provider, we will provide the services requested by the client. We provide a system that recommends suitable outsourcing companies. In this regard, the matching support system 1 considers, for example, the competence and reliability of the agency, and the service requested. We will select a recommended service provider considering the details of the service, costs, etc. Matching support system 1, for example, the actual work of the outsourcing company (diversification of work content, latest The difficulty of keeping up with information, the specialization of outsourcing companies, the differences in difficulty for each task, (Considering the need to provide training opportunities for inexperienced personnel for rear-end upgrades, and to ensure that the service is profitable, etc.) Carefully select an appropriate agency.

[0017] Figure 1 shows a schematic configuration of the matching support system 1. As shown in the figure, The request support system 1 includes a proxy request support device 100, a requester terminal 200, and a proxy service provider. Includes terminal 300. Proxy request support device 100, requester terminal 200, and proxy service provider terminal 30 Each of the 0s is composed of one or more information processing devices (computers) and is part of a communication network. The connection is made via Work 5, enabling bidirectional communication. The communication network 5 is A wired or wireless communication network, such as a LAN (Local Area Network). ), WAN (Wide Area Network), Internet, various public wireless communication networks, dedicated lines, etc. be.

[0018] The proxy request support device 100 receives information regarding the proxy request for the service from the requester terminal 200 ( Hereinafter referred to as "Request Information"), upon receiving the Request Information, the Request Information Select a service provider to perform the services specified in the report. Then, the service request support device 100 will provide information listing the selected agency (hereinafter referred to as "recommended information") Generate and send to client terminal 200.

[0019] The client terminal 200 receives the request from the client and records the received request. The request information is generated and sent to the proxy request support device 100. The requester terminal 200 also... The request support device 100 receives recommendation information and provides the received recommendation information to the requester. Present.

[0020] The agent terminal 300 receives information used by the agent request support device 100 when selecting an agent. (Hereinafter referred to as "agent information") is received from the agent, and the received agent information The information is sent to the proxy request support device 100.

[0021] Figure 2 shows the main functions of the proxy request support device 100. As shown in the figure... The proxy request support device 100 includes a request information receiving unit 110, a request content determination unit 115, and a proxy service provider. Extraction unit 120, agency organization evaluation unit 125, recommendation unit 130, agency request unit 135 , reliability determination table generation unit 140, specialization determination table generation unit 145, agency competence Display unit 150, request evaluation registration unit 155, agent competence database 180, and agent information database It has 185 functions.

[0022] As shown in the figure, the agent competence DB180 is a reliability determination table 1810 and specialized It manages the field determination table 1820. In addition, the agent information DB 185 is a basic information table. It manages Bull 1851, application history table 1852, and request status table 1870.

[0023] Of the above functions, the request information receiving unit 110 receives request information sent from the requester terminal 200. The information is received and stored. The request information is information that identifies the requester (hereinafter referred to as "Requester ID"). (To do so.) Information regarding the specific details of the requested service, and various information necessary for the performance of the service. Includes information.

[0024] The request content determination unit 115 includes a request field determination unit 1151 and a difficulty level determination unit 152. Of these, the request field determination unit 1151 determines the field of the requested service (application) based on the request information. Type, etc. Hereinafter referred to as "request field.") is determined. The request field determination unit 1151 determines, for example If the request information includes information indicating the field of the request, use that information to specify the field of the request. Determine. Also, the request field determination unit 1151 determines, for example, the description (Te) included in the request information. Regarding the quized data, etc., we will apply categorical classification algorithms and natural language processing. Determine the field of the request.

[0025] The difficulty determination unit 152 determines the difficulty level of the request (the service to be provided for the request) based on the request information. The difficulty level of the screw is determined. The difficulty level determination unit 152 determines, for example, the service requested. The difficulty level is determined based on the effort required to provide the service, the amount of work involved, the complexity of the task, the required timeframe (delivery date), etc. Determine the difficulty level. In this embodiment, the difficulty level is one of the following: "low," "medium," or "high." However, difficulty is expressed as a continuous value (the larger the value, the higher the difficulty). The value may also be... The difficulty determination unit 152, for example, if the request information includes information indicating the difficulty level... If available, the difficulty level is determined using that information. Also, the requested field determination unit 1151 However, for example, regarding the description (text data, etc.) included in the request information, a predetermined algorithm The difficulty level is determined by applying rhythm and natural language processing.

[0026] The agent extraction unit 120 has a first extraction unit 1201 and a second extraction unit 1202. The first extraction unit 1201 refers to the confidence determination table 1810 and the basic information table 1 This information lists the selected service providers, chosen based on their reliability, from the list of 851. (Hereinafter referred to as "first extraction result") is generated. The second extraction unit 1202 also specializes in... Refer to field determination table 1820 and select service providers from the first extraction results based on their expertise. The information containing the list of the extracted and selected service providers (hereinafter referred to as "Second Extraction Results") Generate.

[0027] The agency organization evaluation department 125 uses the agency competence DB 180 and agency information DB 185. Based on the contents, the organizations to which the agents listed in the second extraction result belong (for example, law firms) (These include legal offices, judicial scrivener offices, and administrative scrivener offices. Hereinafter referred to as "agency organizations"), Information describing the evaluation results (hereinafter referred to as "evaluation information") is generated, and the generated evaluation information The report is reflected in the request status table 1870. The agency organization evaluation department 125 evaluates, for example, the request. The physical distance from the location of the individual to the location of the agency (the closer the two, the more convenient it is) (Therefore, the rating will also be higher), fees paid to the agency organization (unit price, agency fee, other costs) The agency will be evaluated based on the reputation of the agency, etc. Note that the evaluation information will be shared with users. It may be accepted from the user via the interface, or the agency organization evaluation department 125 may be located It may also be generated based on evaluation using a fixed algorithm or machine learning model. If there are multiple agents within an organization, the agent organization evaluation unit 125 will, for example, evaluate one of them. The evaluation information of the highest-rated outsourcing company is used as evaluation information for the outsourcing company organization in the request status table. Registered in 1870.

[0028] The recommendation section 130 is the agency group to which the agency listed in the second extraction result belongs. The weaving is identified from the basic information table 1851, and the second extraction results and the agency to which each agency belongs are used. The client terminal 200 transmits information including evaluation information of the organization and each of its agents. The terminal 200 receives the above information from the recommendation unit 130 and presents the received information to the user. Furthermore, the client terminal 200 receives the designation of an agent from the user and the designated agent Information identifying the vendor (hereinafter referred to as "Agent ID") and the designated agent organization The information to be identified (hereinafter referred to as the "agency organization ID") is sent to the agency request support device 100. I believe it. The recommendation unit 130 receives the agent ID and agent from the client terminal 200. Receive the operator organization ID.

[0029] When the proxy service provider request unit 135 receives the proxy service provider ID from the requester terminal 200, it checks the request status. Update Table 1870. Also, the agency request department 135 receives the recommendation department 130. The agent terminal 300 of the agent organization to which the agent corresponding to the verified agent ID belongs Information indicating that you are requesting (delegating) the agency to perform the service on your behalf (hereinafter referred to as the "Agency Request Notice"). The agent terminal 300 sends the following to the agent. Upon receiving the agent request notification, the agent terminal 300 sends the following to the agent. Information indicating that a request has been made by the client will be presented. For example, the request notification may include the following: It may include information about the specific details of the service provided.

[0030] The confidence level determination table generation unit 140 generates the confidence level determination table 1810 (editing and deleting). This process includes processing related to ( ). Details of this process will be described later.

[0031] The specialist field determination table generation unit 145 generates a field-specific experience value calculation unit 1451 and specialist field candidates. It has an adult section 1452. The field-specific experience value calculation unit 1451 calculates the experience value of the service provider for each field. The specialist field candidate generation unit 1452 determines the specialist field based on the experience level of the service provider in each field. Create table 1820 (including editing and deleting).

[0032] The agent competence display unit 150 includes a reliability determination table 1810 and a specialization determination table 1 The contents of 820 are sent to the agent terminal 300. The agent terminal 300 then performs a specialization determination test. Receive the contents of the 1820 document and present it to the agent.

[0033] The Request Evaluation Registration Unit 155 receives requests from the requester terminal 200 for information on the agent used by the requester. The evaluation is received, and the received evaluation is reflected in application history table 1852.

[0034] Figure 3 shows an example of the confidence level determination table 1810. The confidence level determination table 1810 includes: The reliability of the outsourcing company is managed. The example reliability determination table 1810 is based on the outsourcing company ID. One or more items having the following characteristics: 1811, Agent Organization ID 1812, and Trust Level 1813 Includes records. One record in the confidence rating table 1810 corresponds to one agent. They are doing it.

[0035] Of the above items, Agent ID 1811 contains the Agent ID (name of the agent, etc.). It will be delivered. Agent organization ID 1812 is the agent organization of the organization to which the agent belongs. The ID (office name, etc.) is stored. Trust level 1813 indicates the trustworthiness of the agency in question. The information is stored. In this example, a value indicating the confidence level (maximum value is 100) is stored. The above value A higher value indicates higher reliability. For details on how the reliability determination table 1810 was generated, please refer to the following. Details will be discussed later.

[0036] Figure 4 shows an example of the specialization determination table 1820. This involves managing information that indicates the areas of expertise and experience of each agency (information that shows the expertise of each agency). The example of the specialist field determination table 1820 is as follows: Agent ID 1811, Agent group One with the following items: Weaving ID 1822, Specialty field 1823, and Experience points for each field 1824. The above records are included. One record in the specialization determination table 1820 is one agent. It is designed to address the needs of the individual.

[0037] Of the above items, the agent ID 1821 stores the agent ID. The organization ID 1822 stores the organization ID of the agency to which the agency belongs. Section 1823 stores information indicating the area of ​​expertise of the agency in question. Experience points for each area. 1824 stores information indicating the agent's experience level in each field. In this example, experience A value indicating the value (maximum value is 100) is stored. The larger the above value, the more experience the user has. This indicates that the person is an expert and highly skilled. (Note: The method for generating the specialization determination table 1820 is described below.) Details of the law will be discussed later.

[0038] Figure 5 shows an example of the basic information table 1850. The basic information table 1850 contains each generation Basic information about the service provider (hereinafter referred to as "basic information") is managed. Examples include: Basic Information Table 1850 includes Agent ID 1851, Agent Organization ID 1852, and Address. One or more records containing the following items: 1853, agency fee 1854, and years of service 1855 Includes "do". One record in basic information table 1850 corresponds to one agent. .

[0039] Of the above items, Agent ID 1851 contains the Agent ID (name of the agent, etc.). It will be delivered. Agent organization ID 1852 is the agent organization of the organization to which the agent belongs. The ID (office name, etc.) is stored here. Address 1853 stores the address of the agency organization in question. The agency fee of 1854 includes the fee (basic fee, additional) for requesting the agency to perform the service. Additional charges etc. are stored. Years of service 1855 are stored in the agency organization of the agency. The length of service (years of employment) is stored here.

[0040] Figure 6 shows an example of the proxy history table 1860. The proxy history table 1860 contains each proxy The service provider's service history is managed. The example service history table 1860 shows service provider ID 1 861, Agency Organization ID 1862, Requested Field 1863, Result 1864, Client Rating Includes one or more records with the fields 1865 and the date of the request for proxy service 1866. Each record in history table 1860 corresponds to one service history of one service provider. .

[0041] Of the above items, Agent ID 1861 contains the Agent ID (name of the agent, etc.). It will be delivered. Agent organization ID 1862 is the agent organization of the organization to which the agent belongs. The ID (office name, etc.) is stored. The field of request 1863 indicates the field of the request. The report is stored. The proxy result 1864 contains the information that the proxy provider performed the proxy request. Information indicating the result (for example, whether the application was "accepted" or "not accepted" by the public institution). Information such as "[...] " is stored. Client evaluation 1865 contains the agency requests handled by the agency. The client's evaluation of the item is stored. In this example, the value indicating the evaluation (maximum value is 100) is used. It will be delivered. A higher value indicates a higher evaluation. On the date of the agency request, 1866, the agency The date on which the person accepted the request for assistance is stored.

[0042] Figure 7 shows an example of the request status table 1870. The request status table 1870 contains requests We accept proxy requests from customers (for which processing by the proxy service provider has not yet been completed after acceptance). Requests are managed. The example request status table 1870 shows requester ID 1871, Request ID 1872, Status 1873, Candidate Requester Information 1874, Requester Information 1875, And include one or more records with the following items: date of request to the agent 1876. Request status One record in table 1870 corresponds to one proxy request received from a client. ru.

[0043] Of the above items, Client ID 1871 contains the client's identifier (client's name, etc.). This is referred to as the "Client ID". Request ID 1872 contains the received proxy request. The identifier (hereinafter referred to as "Request ID") is stored. Status 1873 contains the following information: Information indicating the current status of the request for assistance (e.g., "Waiting for selection of assistance provider," "Request submitted to assistance provider," etc.) This information is stored. The candidate information for the request 1874 contains one or more of the information narrowed down for the request in question. Information regarding potential agents to whom the above request will be made (agent organization name, agent name, agent organization) This section stores evaluation information, fees, etc. The client information 1875 contains the following information regarding the agency request. Information about the agency that was provided (name of the agency organization, agency name, agency organization evaluation information, fees) (etc.) is stored. On the date of the request to the agent, 1876, the processing of the said agent request is handled by the agent. The date the request was made to the service provider is stored here.

[0044] Next, we will explain the various processes performed in Matching Support System 1 in order. .

[0045] Figure 8 shows the process performed in the matching support system 1 (hereinafter referred to as "proxy request support process"). This is a flowchart explaining the process, referred to as "S800". Below, along with the same diagram, is a request for assistance. I will now explain the support process S300.

[0046] First, the requester terminal 200 receives request information from the user via the user interface. The system then sends the received request information to the proxy request support device 100. The request information receiving unit 110 of unit 0 receives request information sent from the requester terminal 200. S811).

[0047] Next, the request field determination unit 1151 determines the request received from the user based on the request information. The request field is determined, and the difficulty level determination unit 1152 determines the request information received from the user. Determine the difficulty level of the request (S812).

[0048] Next, the first extraction unit 1201 uses the confidence determination table 1810 to determine the basic information table Extract potential recommended service providers from Ru1851 and generate the first extraction result (S 813).

[0049] Figure 9 shows the process performed by the first extraction unit 1201 in S813 of Figure 8 (hereinafter referred to as "first extraction process"). This is a flowchart explaining the first extraction, referred to as "Reason S813". The following is a flowchart explaining the first extraction along with the same diagram. I will now explain the output process S813.

[0050] As shown in the figure, first, the first extraction unit 1201, according to the difficulty level determined in S812 The subsequent processing is branched (S911).

[0051] If the difficulty level determined in S812 is "high" (S911: high), the first extraction unit 1201 From the confidence level determination table 1810, if the confidence level 1813 is above the pre-set first threshold, Select a certain agent (S912), and generate a first extraction result that includes a list of the selected agents. This is accomplished (S915). The process then proceeds to S814 in Figure 8.

[0052] Also, if the difficulty level determined in S812 is "medium" (S911: medium), the first extraction unit 1 201 is the second threshold with a pre-set confidence level of 1813, derived from the confidence level determination table 1810. Extract the agents that meet the above criteria but are below the first threshold (S913), and list the extracted agents. The first extraction result, including the specified value, is generated (S915). The process then proceeds to S814 in Figure 8.

[0053] Also, if the difficulty level determined in S812 is "low" (S911: low), the first extraction unit 1 201 is the second threshold with a pre-set confidence level of 1813, derived from the confidence level determination table 1810. Extract agents that are less than (S914), and the first extraction result containing the list of extracted agents The fruit is generated (S915). The process then proceeds to S814 in Figure 8.

[0054] Thus, in the first extraction process S813, the confidence level is determined according to the difficulty of the requested service. The agency that handles this is selected as the first result. For example, for services with high difficulty, Highly reliable service providers are selected, and for services of moderate difficulty, the reliability is... Mid-level service providers were selected, and for services with low difficulty, less reliable service providers were selected. The vendors are selected.

[0055] Returning to Figure 8, the second extraction unit 1202 of the agent extraction unit 120 then performs a specialization field determination test. Based on the 1820 code, the second selection result is generated by extracting the agents from the first selection result. S814).

[0056] Figure 10 shows the process performed by the second extraction unit 1202 in S814 of Figure 8 (hereinafter referred to as "second extraction"). This is a flowchart explaining process S814. The following section, along with the same diagram, is titled "Second..." The extraction process S814 will now be explained.

[0057] First, the second extraction unit 1202 branches the subsequent processing according to the difficulty level determined in S812. Cell (S1011).

[0058] If the difficulty level determined in S812 is "high" or "medium" (S1011: high or medium), The second extraction unit 1202 extracts from the specialization field determination table 1820, based on the results of the first extraction, Furthermore, extract the service providers whose specialized fields include the requested field and generate a second extraction result. S1012, S1014). The process then proceeds to S815 in Figure 8.

[0059] Furthermore, if the difficulty level determined in S812 is "low" (S1011: low), the second extraction unit 1202 is listed in the first extraction result from the specialization determination table 1820, and is requested The second selection results are generated by extracting service providers whose experience level in the field is below a predetermined threshold. This is accomplished (S1013, S1014). After that, the process proceeds to S815 in Figure 8.

[0060] Thus, in the second extraction process S814, services with a difficulty level of "high" or "medium" are selected. Therefore, from among the agents with a reliability rating of "high" or "medium" that were extracted as the first result of the selection process, The system extracts service providers whose expertise includes the requested field. Additionally, it categorizes services as "low difficulty." Therefore, from among the service providers with a "low" reliability rating that were selected as the first selection result, the service provider in question The system will select outsourcing companies with little experience in the specific area of ​​the request for screws.

[0061] Returning to Figure 8, the next step is for the agency organization evaluation department 125 to evaluate the agencies to which the second selection results belong. The agency organization is identified from the basic information table 1851, and the agency competence DB 180 and the agency Based on the contents of the service provider information DB185, evaluation information for the identified service provider organization is generated. Furthermore, the agency organization evaluation department 125 reflects the generated evaluation information in the request status table 1870. do (S815).

[0062] Next, the recommendation department 130 will present the second extraction results, the identified agency organizations, and each agency. Recommendation information, including evaluation information of the organization, is sent to the requester terminal 200. Unit 130 updates status 1873 in request status table 1870 (S816) .

[0063] The client terminal 200 receives recommendation information sent from the recommendation unit 130. The received recommendation information is presented to the user. Furthermore, the client terminal 200 is connected to the agency organization. The system accepts requests from users to specify an agent, and the accepted agent ID and agent organization ID are used. The request is sent to the proxy request support device 100. The recommendation unit 130 receives the request from the requester terminal 200. The system receives the agent ID and agent organization ID (S817).

[0064] The agency request department 135 receives agency agency organization IDs from the agency agency department 130. A request notification for outsourcing is sent to the organization's outsourcing agent terminal 300. Also, the outsourcing agent request unit 135, Update status 1873 in request status table 1870 (S818).

[0065] When the proxy service provider terminal 300 receives a proxy request notification, it notifies the proxy service provider that a proxy request has been made. The agent will present the information. The agent will perform the services specified in the agent request notice (S819). .

[0066] As described above, according to the proxy request support process S800, the difficulty level is "high" or "medium". For the screws, highly reliable and knowledgeable (highly specialized) outsourcing companies were selected. Therefore, for services of "high" or "medium" difficulty, a representative who is well-versed in the requested field will be assigned. An organization of service providers that meets the needs of clients who want to receive highly reliable services from service providers. It can also recommend an agency to the client. Furthermore, for the agency, it can be a way to leverage their expertise. The likelihood of receiving requests in the relevant fields increases, allowing us to leverage our expertise to provide high-quality services. This can be achieved. In addition, this increases client satisfaction, which in turn satisfies the agency. You can expect a return.

[0067] Furthermore, for services with a "low" difficulty level, we select from among less reliable outsourcing companies based on experience. Shallow service providers are selected. Therefore, for services with a "low" difficulty level, reasonable... We can provide services quickly at reasonable prices (because we can search a wide range of service providers with ample capacity to provide services quickly). (In the sense that the likelihood of being able to provide the service increases) in line with the needs of clients who want to enjoy the service. It can recommend the agency that performed the task. Also, for agency organizations and agencies This allows for effective utilization of human resources (improved work efficiency) and enhances the careers of less experienced individuals. Benefits such as the ability to (educate) can be expected.

[0068] <Generating a confidence level determination table> Figure 11 shows the reliability determination table generation unit 140 of the proxy request support device 100, which determines the reliability The process performed when generating table 1810 (hereinafter referred to as "reliability determination table generation process S11") This is a flowchart explaining the reliability assessment method, referred to as "00". The following is a flowchart explaining the reliability assessment method, along with the same diagram. The table generation process S1100 will be explained below. Processing S1100 is performed on the agent (agent ID 185) in the basic information table 1850. 1) Each one is added.

[0069] First, the confidence level determination table generation unit 140 generates the corresponding information from the basic information table 1850. Obtain basic information of the target agent (hereinafter referred to as "the agent") (S11 11).

[0070] Next, the reliability determination table generation unit 140 generates the proxy history table 1860, and then the proxy Retrieve the record information of the service provider (the service provider's service history) (S1111).

[0071] Next, the confidence level determination table generation unit 140 selects the relevant field from the expertise field determination table 1820. Obtain the experience level of the outsourcing company in each field (S1113).

[0072] Next, the reliability determination table generation unit 140 calculates the reliability of the agency (S1 114). The confidence level determination table generation unit 140 generates, for example, the following formula (hereinafter referred to as "Formula 1") The confidence level is calculated based on ( ). [Mathematics 1] Reliability = Average of the experience levels of the service providers in each field, as determined by the expertise assessment table. + Points based on the number of applications + Points based on the acceptance rate (= number of accepted applications / total number of applications to date)

[0073] The confidence level determination table generation unit 140 calculates the second term in Equation 1, "score based on the number of applications". For example, Table 1 shown in Figure 12A (hereinafter referred to as "Application Number and Score Correspondence Table 1210"). The reliability determination table generation unit 140 calculates based on the third term of Equation 1, "Selection The score is based on the acceptance rate (= number of accepted applications / total number of applications to date), for example, as shown in Table 2 in Figure 12B. The following will be referred to as "Correspondence Table 1220 between Acceptance Rate and Score."

[0074] Next, the reliability determination table generation unit 140 generates the agent ID of the agent, and the agent The organization ID of the agency to which the vendor belongs, and the reliability score obtained in S1214 are associated with this ID. The code is generated and stored (registered) in the confidence level determination table 1810 (S1215).

[0075] <Generating a Specialty Field Determination Table> Figure 13 shows that the specialist field determination table generation unit 145 of the proxy request support device 100 determines the specialist field The process performed when generating the judgment table 1820 (hereinafter referred to as "specialized field judgment table generation process") This is a flowchart explaining the "S1300" (as it is called). Below, along with the same diagram, the specialized fields The judgment table generation process S1300 will be explained. S1300 is performed for each agent (agent ID 1851) in the basic information table 1850. It can be done.

[0076] First, the specialization field determination table generation unit 145 processes the basic information table 1850. Obtain basic information of the target agency (hereinafter referred to as "the agency") (S1 311).

[0077] Next, the reliability determination table generation unit 140 generates the proxy history table 1860, and then the proxy Retrieve the record information of the service provider (the service provider's service history) (S1312).

[0078] Next, the confidence level determination table generation unit 140 generates the relevant data from the confidence level determination table 1810. Obtain the reliability rating of the service provider (S1313).

[0079] Next, the reliability determination table generation unit 140 calculates the experience level of the relevant service provider for each field. (S1313). The specialization field determination table generation unit 145 generates, for example, the following equation (hereinafter referred to as "Equation 2"). It is called "..." and the experience level for each field is calculated based on this. [Math 2] Experience in the field of XX = Points based on the number of applications submitted by the agency in the XX field within the application history table. + Points based on the acceptance rate in the XX field (= number of accepted applications / total number of applications to date) +Score based on the average client evaluation in the XX field

[0080] Furthermore, the specialist field determination table generation unit 145 generates the first item in Equation 2, "within the application history table". The "points based on the number of applications in the XX field by the agency" can be used, for example, as shown in Table 1 (Applications) in Figure 12A. The results are determined based on the correspondence table between the number of cases and the score (1210). Furthermore, the specialized field determination table generation unit 14 5 is the second term in Equation 2, "Acceptance rate in the XX field (= number of accepted applications / total number of applications to date)," for example. For example, it is determined based on Table 2 (Correspondence Table 1220 between acceptance rate and score) shown in Figure 12B. The field determination table generation unit 145 generates the third term in Equation 2, "Average of client evaluations in the XX field". "Scores based on values" are, for example, shown in Table 3 in Figure 12C (hereinafter referred to as "Average values ​​and scores of client evaluations"). This is referred to as "Correspondence Table 1230." The result is obtained based on this table.

[0081] Next, the specialist field determination table generation unit 145 generates a table from which the confidence level obtained in S1313 is pre-set. Determine whether the value is above a predetermined threshold (S1315).

[0082] If the confidence level is above a predetermined threshold (S1315: YES), the expert field determination table The Bull generation unit 145 sends all field names and the experience values ​​obtained for each field to the service provider terminal 300. To believe (S1316). The agent terminal 300 receives from the agent request support device 100. While presenting all the field names and the required experience level for each field, we also ask the agency which field they would like to specialize in. The system accepts input of (specialized field) and transmits the accepted field to the proxy request support device 100. S1331). The specialist field determination table generation unit 145 receives the field from the agent terminal 300. Upon confirmation, the agency ID of the agency and the agency's affiliation will be added to the specialty determination table. The agency ID of the organization, the field received from the agency terminal 300, and in S1314 Records are generated that associate the required experience points in each field and are stored in the specialization determination table 1820. Store (register) (S1317).

[0083] In S1315, if the confidence level is below a predetermined threshold (S1315: NO) The specialist field determination table generation unit 145 generates the specialist field determination table for the agency of the agency. The vendor ID, the vendor organization ID of the organization to which the vendor belongs, and each of the items obtained in S1314 Records that associate experience in a field (in this case, the field 1823 is not listed) Generate and store (register) in the specialization determination table 1820 (S1321).

[0084] Figure 14AB shows that in S1331, the agent terminal 300 specifies the field (specialized field) to the agent. The screen displayed when accepting applications (hereinafter referred to as "Specialized Field Application Screen 1410") Here is an example.

[0085] <Processing of the agent's competence display section> The agent competence display unit 150 of the agent request support device 100 is managed by the agent competence DB 180. Based on the information being managed (reliability determination table 1810, specialty determination table 1820) The screen (hereinafter referred to as "capabilities") describes the capabilities of the outsourcing company (reliability, area of ​​expertise, experience in each field). It generates and presents to the user a screen called "Quantity Information Confirmation Screen 1420".

[0086] Figure 14B shows an example of the competency information confirmation screen 1420. Note that the agent competency display unit 150 However, the competency information confirmation screen 1420 can be sent to the agent's terminal 300 so that the agent can refer to it. You may do so. The agent can check their own competence by referring to the competence information confirmation screen 1420. You can check what kind of information is registered in the proxy request support device 100. .

[0087] <Requested Evaluation Registration Department> The request evaluation registration unit 155 of the proxy request support device 100 evaluates the services performed by the proxy service provider. The evaluation is received from the client via the client terminal 200, and the received evaluation is recorded in the proxy history system. This will be reflected in the 1860 edition of the brochure.

[0088] Figure 15 shows the screen displayed on the client terminal 200 when receiving an evaluation from the client (hereinafter, An example of what is called "Request Evaluation Acceptance Screen 1500" is shown below.

[0089] <Example of an information processing device> Figure 16 shows the configuration of the matching support system 1 (including the proxy request support device 100 and the requester terminal 2). Hardware of the information processing device (computer) used for realizing the proxy terminal 300 A is an example configuration.

[0090] The example information processing device 10 includes a processor 11, main memory 12 (memory), and auxiliary storage. The system includes a device 13 (external storage device), an input device 14, an output device 15, and a communication device 16. These are connected in a way that allows communication via buses, communication cables, etc. Information processing device 10 Examples include personal computers, server equipment, smartphones, tablets, and office equipment. These include computer computers and general-purpose machines (mainframes).

[0091] The information processing device 10 is provided, in whole or in part, by, for example, a cloud system. Virtual servers, like virtual servers, are provided using virtualization technologies and process space isolation technologies. It may also be implemented using information processing resources. All or part of the functions provided are, for example, provided by the cloud system via API (Application). This may also be implemented through services provided via a Programming Interface, etc. All or part of the functions provided by the information processing device 10 may be, for example, SaaS (Software as a Service). PaaS (Platform as a Service), IaaS (Infrastructure This may also be implemented using methods such as (as a Service).

[0092] Processor 11 includes, for example, a CPU (Central Processing Unit) and an MPU (Micro Processor). processing unit), GPU (Graphics Processing Unit), FPGA (Field Programmable Gate Array), ASIC (Application Specific Integrated Circuit), AI (Artifi It is composed using (social intelligence) chips, etc.

[0093] The main memory 12 is a device used by the processor 11 when executing a program. For example, ROM (Read Only Memory), RAM (Random Access Memory), non-volatile memory. Examples include NVRAM (Non-Volatile RAM), etc. This includes the proxy request support device 100 and the requester terminal. The various functions implemented in the 200 and the proxy terminal 300 are performed by the respective processors 11 The program and data stored in the auxiliary storage device 13 are read into the main memory device 12. It is achieved by breaking away from the norm and executing it.

[0094] The auxiliary storage device 13 is a device for storing programs and data, for example, an SSD (So (Limited State Drive), hard disk drive, optical storage device (CD (Compact Disc)) DVDs (Digital Versatile Discs), storage systems, IC cards, SD cards Read / write devices for non-temporary recording media such as optical recording media, and non-temporary cloud servers. It can be configured with a typical memory area, etc. The auxiliary storage device 13 includes a recording medium reader and Other information processing via the communication device 16, including non-temporary recording media and non-temporary storage devices. The device can read programs and data. These are stored in the auxiliary storage device 13. The programs and data being stored are loaded into the main memory 12 as needed.

[0095] The input device 14 is an interface that accepts information input from the outside, for example, Keyboard, mouse, touch panel, card reader, pen input tablet, voice input These are power devices, etc.

[0096] The output device 15 is an interface that outputs various information such as processing progress and processing results to the outside. Yes. The output device 15 is, for example, a display device (LCD monitor, L) that visualizes the various information mentioned above. CD (Liquid Crystal Display), graphics card, etc.), and the above various information are converted into audio. A device for outputting audio (speaker, etc.), and a device for converting the above information into text (printing device, etc.) ) Furthermore, for example, information processing device 10 can exchange information with other devices via communication device 16. It may also be configured to handle input and output.

[0097] The input device 14 and output device 15 perform interactive processing with the user (receiving information, information Configure a user interface to realize (such as providing) the service.

[0098] The communication device 16 is a device that enables communication with other devices. Wired or wireless communication methods that enable communication between devices via a network. It is an interface, such as a NIC (Network Interface Card) or wireless communication module. These include USB modules, etc.

[0099] Furthermore, the information processing device 10 includes, for example, an operating system, a file system, DBMS (Database Management System) (relational database, NoSQL, etc.) ), or a KVS (Key-Value Store), etc., may be implemented.

[0100] [Second Embodiment] In the matching support system 1 of the first embodiment, from the perspective of reliability and field (specialized field), We extracted the agencies that we recommend to the client. Matching support system 1 of the second embodiment Furthermore, the number of service providers will be selected based on the amount of work required to perform the service. The form matching support system 1 allows multiple agents to share the service for a single request. We will select a service provider, taking into consideration the possibility of carrying out the task together. In this way, the matching of the second embodiment The support system 1 extracts recommended outsourcing companies considering the workload, so the workload If a third-party service provider is recommended who cannot secure the necessary resources, the client may be refused service by the third-party service provider. This can reduce the likelihood of situations like these occurring.

[0101] The matching support system 1 of the second embodiment receives request information from clients regarding the agency request. Based on the information, calculate the amount of work required to perform the requested service, categorized by difficulty level. The matching support system 1 then stores the workload for each difficulty level separately for each agent. We select the appropriate outsourcing companies by comparing their respective workloads with the workloads they can handle within the organization.

[0102] Figure 17 shows the proxy request support device 100 of the matching support system 1 of the second embodiment. This figure shows the main functions. The proxy request support device 100 of the second embodiment is the same as that of the first embodiment. The proxy request support device 100 and the first embodiment share the same basic configuration, but differ in the following respects. The configuration differs from that of the proxy request support device 100.

[0103] First, the processing of the difficulty determination unit 1152 in the request content determination unit 115 is different. Also, the request content The configuration differs in that the determination unit 115 further includes a work amount determination unit 1153. Also, the first extraction unit The 1201 and the second extraction unit 1202 differ in their configuration in that they process information according to its difficulty level. Furthermore, the configuration differs in that the agent extraction unit 120 further includes a third extraction unit 1203. Furthermore, the workload determination table 180 used by the service provider competence DB180 to determine the workload of the service The structure differs in that it manages 30. Also, the agency request department 135 receives requests from agencies. Regarding this, the available time is calculated from the record of the relevant contractor in the workload determination table 1830. The structure differs in that it deducts the time required for the task by the amount of work involved. The configuration differs in that it further includes the adult section 190. Below, the proxy request support device of the first embodiment is described. This explanation will focus on the differences from the 100 model.

[0104] The difficulty determination unit 1152 of the proxy request support device 100 in the second embodiment determines the difficulty level for each element of the service. The difficulty level is determined for each item in the application form (for example). The difficulty level determination unit 1152 determines the result The system generates and manages (stores) difficulty assessment results that include the outcome. Note that the difficulty assessment is determined by the user. You may proceed, or the difficulty determination unit 1152 may automatically determine it based on the request information. For example, the acceptance rate of past applications (the lower the acceptance rate, the higher the difficulty level, etc.), the amount of information to be written in the application form (notes) (The more content there is, the higher the difficulty level, etc.), the amount of free-response text (the more free-response text there is, the higher the difficulty level) The difficulty level is determined based on factors such as (etc.).

[0105] Figure 18A shows the difficulty level determination unit 1152 and the contents of application form 1805 included in the request information. Based on this, the difficulty level is determined for each element (item) and the difficulty level determination result 1801 is generated. show.

[0106] Returning to Figure 17, the workload determination unit 1153 of the proxy request support device 100 determines the workload based on the request information. Determine (estimate) the amount of work required to perform the service requested. (Workload Determination Unit) 1153 determines the amount of work required for the requested service based on the difficulty level determined for each element. The quantity determination unit 1153 generates and manages (stores) the work quantity determination result, which contains the determined result. ru.

[0107] Figure 18B shows the workload determination unit 1153 determining the difficulty level for each element and the services requested. This shows how the amount of work done is determined and the work amount determination result 1802 is generated.

[0108] Returning to Figure 17, the third extraction unit 1203 refers to the workload determination table 1830 and requests From the second selection results, we extracted combinations of outsourcing companies capable of performing the specified tasks. A third extraction result is generated, which contains the results of the above process.

[0109] The workload determination table generation unit 190 of the proxy request support device 100 in the second embodiment is used for proxy services. The work schedule (already scheduled work date / time / work period) is communicated via terminal 300 to the service provider. The system accepts the workload and generates a workload determination table 1830 based on the accepted work schedule. (Including editing, deleting, etc.)

[0110] Figure 19 shows that the workload determination table generation unit 190 generates the work volume determination table from the outsourcing company terminal 300. The screen displayed when accepting work schedules (hereinafter referred to as "Work Schedule Acceptance Screen 1900"). This is an example. The work schedule acceptance screen 1900 may be generated by the agent terminal 300. Alternatively, the proxy request support device 100 may generate and transmit the request to the proxy service provider terminal 300.

[0111] Figure 20 shows the work volume determination table generation unit 190 that generates the work volume determination table based on the received work schedule. This is an example of the workload determination table 1830. As shown in the figure, the workload determination table 183 0 represents the agent ID 1831, agent organization ID 1832, and the amount of work for each available work period. It consists of one or more records, each containing one of the 1833 items. Workload Determination Table 183 One of the records with a value of 0 corresponds to one service provider.

[0112] Of the items listed above, Agent ID 1831 stores the Agent ID of the agent in question. The agency organization ID 1832 is the agency organization ID of the organization to which the agency belongs. It is stored. The amount of work per available period 1833 is the amount of work per available period (hours (h) The units are stored.

[0113] Figure 21 shows the process performed in the matching support system 1 of the second embodiment (hereinafter, This is a flowchart explaining the "Proxy Request Support Process S2100". Regarding the processing of S2111 within the support processing S2100, the proxy request support processing S is shown in Figure 8. For S811 of 800, and also for S2117~S2119, see the proxy request support shown in Figure 8. Although it is the same as S817~S819 of support processing S800, the processing of S2112~S2116 This differs from the proxy request support process S800 shown in Figure 8. The proxy request support process S80 is described below. Centering on the differences from 0, together with the figure, the proxy request support process S2100 of the second embodiment will be described.

[0114] In S2112, the request field determination unit 1151 determines the field of the requested service (type of application form etc.), and the difficulty determination unit 1152 determines the difficulty for each element of the service (for example, for each item of the application form) by the method described above. Note that the proxy request support device 100 stores the determined field and the difficulty for each element as the difficulty determination result 1801 (S812).

[0115] In S2113, the proxy agent extraction unit 120 (the first extraction unit 1201, the second extraction unit 1202) performs processing for each level of difficulty in the difficulty determination result 1801, and generates the first extraction result and the second extraction result (hereinafter referred to as the "third extraction process S2113").

[0116] FIG. 22 is a flowchart for explaining the third extraction process S2113. Hereinafter, the third extraction process S2113 will be described together with the figure. Note that the figure corresponds to the processing for a certain level of difficulty "x". That is, the third extraction process S2113 is executed for each level of difficulty.

[0117] As shown in the figure, first, the proxy agent extraction unit 120 obtains the workload for the level of difficulty "x" determined by the difficulty determination unit 1152 (S2211).

[0118] Subsequently, the proxy agent extraction unit 120 determines whether the obtained workload is greater than "0" (S2212). If the workload is not greater than "0" (S2212: NO), the third extraction process S2113 for this level of difficulty ends. If the workload is greater than "0" (S2 212: YES), the process proceeds to S2213.

[0119] In S2213, the first extraction unit 1201, with the difficulty level set to "x", performs the first extraction shown in Figure 9. The output process S813 is performed to generate the first extraction result.

[0120] Next, the second extraction unit 1202 performs the second extraction process shown in Figure 10, with the difficulty level set to "x". Perform S814 to generate the second extraction result (S2214).

[0121] Next, the third extraction unit 1203 selects a contractor based on the results of the second extraction, taking into account the workload. The process of extracting data and generating a third extraction result that describes the extracted data (hereinafter referred to as "third extraction result generation") This process is called "processing S2215".

[0122] Figure 23 is a diagram illustrating the outline of the third extraction result generation process S2215. The following discussion will refer to the same figure. We will now explain the outline of the third extraction result generation process S2215.

[0123] First, the third extraction unit 1203 selects from the workload determination table 1830 the number of items with a difficulty level of "x". 2. Extract records containing the agent ID from the extraction results (S2311). In the example shown in the figure, From agency organization α, we obtained records for three agents α1 to α3, and from agency organization β, we obtained records for two agents α1 to α3. We are extracting records from human service providers β1 and β2.

[0124] Next, the third extraction unit 1203 is selected from among those belonging to the same agency organization (with the same agency organization ID). (i) Group the records of the service providers (S2312). In the example shown in the figure, service provider α Records 1-α3 are placed in Group A1, records from agent β1-β2 are placed in Group A2, husband They are grouped together.

[0125] Subsequently, the third extraction unit 1203 adds a record of the combination of ai" to the third extraction result with the difficulty level "x". Here, when i" is the number of people in the small group formed from i' within the group Ai, it represents the position of the combination a of the small group consisting of i' people.

[0126] Subsequently, the third extraction unit 1203 generates all combinations a1, a2,..., ai",..., an" of i' people within Ai (S2314). Here, n is the total number of groups A for each proxy organization, and n" is the total number of combinations a.

[0127] Subsequently, the third extraction unit 1203 calculates the total workload within the specified period of the proxy workers included in ai" (S2315).

[0128] Subsequently, the third extraction unit 1203 stores the combination of ai" in the third extraction result with the difficulty level "x" (S2316).

[0129] In the figure, an example is shown where the difficulty level of the requested service is "medium", the workload is "30", i' is "2", the available working hours of proxy worker α1 is "10", the available working hours of proxy worker α2 is "20", and the available working hours of proxy worker α3 is "10". In this case, for the combinations "a1" and "a2" shown within the thick frame in the figure, since the total available working hours of the proxy workers is 30 or less, the work can be performed. Therefore, the third extraction unit 1203 stores the records corresponding to each combination of (α1, α2) and (α2, α3) in the third extraction result with the difficulty level "medium".

[0130] Figure 24 is a flowchart for explaining the third extraction result generation process S2215. Hereinafter, ​​​​​​​​​​​The third extraction result generation process S2215 will be explained along with the figure.

[0131] First, the third extraction unit 1203 extracts the second extraction result for difficulty level "x", the period, and the creation of difficulty level "x". Acquire business volume (S2411).

[0132] Next, the third extraction unit 1203 extracts the second result of difficulty level "x" from the workload determination table. Extract records that contain the proxy provider ID (S2412).

[0133] Next, the third extraction unit 1203 searches the extracted records for the same agency organization ID. Group each record (generate A1, A2, ..., Ai, ..., An) (S241 3).

[0134] Next, the third extraction unit 1203 sets the index i to "1" (S2414).

[0135] Next, the third extraction unit 1203 determines whether i is less than or equal to n (S2415). If n is less than or equal to (S2415: YES), the process proceeds to S2416. On the other hand, if i is greater than n If the result is not met (S2415:NO), the third extraction result generation process S2215 is terminated.

[0136] Next, the third extraction unit 1203 obtains the number of people n' (total number of people in Ai) in Ai (S2416). .

[0137] Next, the third extraction unit 1203 sets i' to "1" (S2417).

[0138] Next, the third extraction unit 1203 determines whether i' is less than or equal to n (S2418). If the condition is lower (S2418:YES), the process proceeds to S2419. On the other hand, if i' is greater than n In the case of (S2418:NO), add "1" to i (increment), and then the process is S Return to 2415.

[0139] In S2419, the third extraction unit 1203 extracts all combinations of i' people within Ai, "a1, a2, ... This generates "...ai", "...an".

[0140] Next, the third extraction unit 1203 sets i" to "1" and the workable flag to "0 Set " (S2421).

[0141] Next, the third extraction unit 1203 determines whether i" is less than or equal to n" (S2418). If the following is true (S2418: YES), the process proceeds to S2423. On the other hand, if i" is greater than n" If the answer is no (S2418:NO), the process proceeds to S2430.

[0142] In S2423, the third extraction unit 1203 is within the period specified by the agent included in "ai" Calculate the total amount of work to be done.

[0143] Next, the third extraction unit 1203 determines whether the total amount of work is equal to or greater than the amount of work corresponding to difficulty level "x". Determine (S2424). If the total amount of work is equal to or greater than the amount of work for difficulty level "x", then (S242 4ES), processing proceeds to S2425. Meanwhile, if the total workload is less than the workload for difficulty level "x" If (S2424:NO), the process proceeds to S2427.

[0144] In S2425, the third extraction unit 1203 combines the third extraction result for difficulty level "x" with "ai". Add a note.

[0145] Next, the third extraction unit 1203 sets the workable flag to "1" (S2426).

[0146] Next, the third extraction unit 1203 adds (increments) "1" to i", and then processes The logic returns to S2418.

[0147] In S2430, the third extraction unit 1203 determines whether the workable flag is "1" or not. If the workable flag is "1" (S2430:YES), the third extraction unit 1203 sets i to " The value is incremented by 1 (S2431), and then the process returns to S2415. On the other hand, if the workable flag is not "1" (S2430:NO), the third extraction unit 1203 will, The value is incremented by "1" (S2431), and then the process returns to S2418. .

[0148] Returning to Figure 21, the agent extraction unit 120 then determines the fourth extraction result based on the third extraction result. The process to generate 174 (hereinafter referred to as "the fourth extraction result generation process S2114") is performed. (S2114).

[0149] Figure 25 is a flowchart illustrating the fourth extraction result generation process S2114. The following describes the process. The fourth extraction result generation process S2114 will be explained along with the figure.

[0150] First, the contractor extraction unit 120 determines the third difficulty level of each of the work volume determination results 1802 in Figure 18B. Retrieve the extraction results (S2511).

[0151] Next, the agent extraction unit 120 determined that agent organization I was included in the third extraction result for all difficulty levels. Remove records where D does not exist from all third extraction results (S2512).

[0152] Next, the agent extraction unit 120 performs the third extraction results for each difficulty level for each agent organization. The records corresponding to each combination obtained by selecting one agent at a time from the list are Generate the record and store it in the fourth extraction result 174 (S2513).

[0153] As described above, the matching support system 1 of the second embodiment performs the service The selection of outsourcing companies will take into account the amount of work required, so for example, if the amount of work cannot be secured, This allows for the recommendation of an agency and prevents situations where the agency refuses to handle the request. Furthermore, the matching support system 1 of the second embodiment provides multiple services for a single request. A number of agents (each agent does not need to belong to the same agency organization) collaborate to complete the task. When selecting a service provider, you can also consider the possibility of performing the task yourself.

[0154] [Third Embodiment] When matching clients with service providers, for example, if a client has a bad reputation... I would prefer not to accept requests from clients that could lead to trouble. If you wish that the agency could choose which clients they want to work with, for example, if you don't want to accept a particular request. There are such agents. In order to meet the needs of such agents, the matching support system of the third embodiment System 1 will further incorporate a mechanism for evaluating clients from the service providers. Specifically, the third implementation will be implemented in The matching support system 1 accepts evaluations of clients from agency providers, and the agency provider For clients who do not meet the level they registered in advance, the agency will not provide the service to that client. Avoid recommending vendors.

[0155] Figure 26 shows the third embodiment, which is configured based on the proxy request support device 100 of the second embodiment. This shows the main functions of the proxy request support device 100 in the status matching support system 1. This is a diagram. The function of the proxy request support device 100 of the third embodiment is the same as the proxy request support of the second embodiment. The functions and basic configuration of the support device 100 are the same, but in the following respects, it is a substitute for the second embodiment. The configuration differs from that of the request support device 100.

[0156] First, the proxy request support device 100 of the third embodiment includes a requester information DB 170 and a requester It further has the functions of a level registration unit 191 and a client evaluation registration unit 192. Report DB170 contains the client evaluation table 1710, which stores the client's evaluation by the agency. It manages the following: Also, the basic information table managed by the agent information DB185 of the third embodiment. In 1850, the agency's desired level of client (hereinafter referred to as "desired client level") An item for storing ( ) has been added. Also, the proxy request support device 100 of the third embodiment The recommendation section 130 states that for clients who do not meet the desired client level of the agency, We will not recommend this agency to the client.

[0157] Among the functions of the proxy request support device 100 of the third embodiment, the desired requester level registration unit 191 The system receives the desired client level setting from the agent via the agent terminal 300. The assigned desired client level is stored in the basic information table 1850.

[0158] Figure 27 shows when the desired client level registration unit 191 accepts the setting of the desired client level. The screen displayed by the agent terminal 300 (hereinafter referred to as the "Requested Client Level Reception Screen 2700") This is an example of what to do.

[0159] Figure 28 shows an example of the basic information table 1850 of the third embodiment. As shown in the figure... In addition to the items mentioned above, the basic information table 1850 of the third embodiment includes the desired requester level. It further includes the entry for Ru1856.

[0160] The client evaluation registration unit 192 shown in Figure 26 receives requests from agents via the agent terminal 300. We accept requests to set an evaluation of the client (hereinafter referred to as the "Client Evaluation Level") and accept the request. The contents are registered in the client evaluation table 1710. Note that if the same client makes multiple requests... If the agency has received such a request in the past, the agency will, for example, provide information about each past request to the client. The average of the evaluations given by the client in question is set as the client evaluation level.

[0161] Figure 29 shows an example of client evaluation table 1710. As shown in the figure, client evaluation Table 1710 contains the fields for Client ID 1711 and Client Evaluation Level 1712. It consists of one or more records. The requester ID 1711 stores the requester ID. Client evaluation level 1712 stores the client evaluation level.

[0162] The recommendation unit 130 of the proxy request support device 100 in the third embodiment is based on the basic information table 1 The 850 desired client levels (1856) are compared with the client evaluations in the client evaluation table (1710). Furthermore, even if an agent is selected by the agent selection unit 120, the agent's preferred client For clients who do not meet the required level, we will not recommend the agency in question to them.

[0163] As described above, the matching support system 1 of the third embodiment provides evaluations of the client from the agent. We accept bids, and for clients who do not meet the level that the agent has registered in advance, We will not recommend the agency in question to the client. For example, if the agency has a poor reputation I would prefer not to accept requests from clients that could lead to trouble. This allows us to accommodate the wishes of agencies that do not want to accept the job.

[0164] Furthermore, the above describes the third embodiment based on the proxy request support device 100 of the second embodiment. The case in which the checking support system 1 is configured has been described, but the same method can be used as a substitute for the first embodiment. Even if the matching support system 1 of the third embodiment is configured based on the request support device 100, good.

[0165] Although embodiments have been described above, the present invention is not limited to the embodiments described above. This includes various variations and is not necessarily limited to those that possess all the configurations described. No. Also, replacing a part of the configuration of one embodiment with the configuration of another embodiment, Furthermore, it is possible to add the configuration of one embodiment to the configuration of another embodiment. It is possible to add, delete, or replace other components in the configuration of the installation form.

[0166] For example, the services that a client seeks from a service provider include financial institutions and infrastructure. Services provided to businesses (electricity companies, gas companies, telecommunications companies, etc.), hospitals, etc. Furthermore, services include, for example, the search and distribution of information and services, the verification of the authenticity of information, and information This could include obtaining consent when using the service, or simplifying the complexities of various procedures. [Explanation of symbols]

[0167] 1. Matching Support System 5. Communication Network 100 Proxy Request Support Device 110 Request Information Receiving Unit 115 Request Content Determination Unit 1151 Request Field Determination Unit 1152 Difficulty level judgment section 1153 Work amount judgment section 120 Agency Extraction Department 1201 1st extraction part 1202 Second extraction part 1203 Third extraction part 125 Agency Organization Evaluation Department 130 Recommendation Department 135 Agency Request Department 140 Confidence Determination Table Generation Unit 145 Specialty Field Determination Table Generation Unit 1451 Field-Specific Experience Calculation Unit 1452 Specialized Field Candidate Generation Unit 150 Agency competency display section 155 Request Evaluation Registration Department 170 Client Information Database 1710 Client Evaluation Table 180 Agency competency DB 1801 Difficulty judgment result 1802 Work amount judgment result 1805 Application form 1810 Confidence Level Determination Table 1820 Specialty Field Determination Table 1830 Workload Determination Table 185 Agency information DB 1850 Basic Information Table 1860 Proxy History Table 1870 Request Status Table 190 Workload Determination Table Generation Unit 191 Desired Client Level Registration Department 192 Client Evaluation and Registration Department 200 Client terminals 2700 Request Level Request Screen 300 proxy service terminals

Claims

1. When a requester requests a service provider to provide a service, the requester and the service provider A system for supporting matching between providers, The information processing device includes a processor and a storage device, basic information relating to each of the plurality of providers; Request information, which is information regarding the request received from the requester; A reliability level, which is information indicating the degree of reliability of each of the plurality of providers; and information indicating the expertise of each of the providers in the service; Remember, a difficulty level determination unit that determines the difficulty level of the request based on the request information; The provider having a higher reliability is extracted for the request having a higher degree of difficulty. A first extraction result listing candidates for service providers extracted from the basic information and the extracted results. a first extractor for producing a fruit; The more difficult the request, the more specialized the provider of the service. The service provider candidates are extracted from the first extraction result, and the extracted a second extraction unit that generates a second extraction result that describes the result; A matching support system that includes:

2. The matching support system according to claim 1, The reliability is determined based on the provider's experience in each field of the service, the number of cases in which the service is provided, and other factors. and the success rate of the service, Matching support system.

3. The matching support system according to claim 1, The level of expertise is determined based on the provider's experience in each field of the service, the division of the service, etc. The number of services provided by each field, the client's evaluation of the services provided, and the services received from the provider identified based on at least one of the areas of expertise they have acquired, Matching support system.

4. The matching support system according to claim 1, The provider candidates based on the second extraction result are displayed on the requester via a user interface. Recommendation section to present to customers, A matching support system further comprising:

5. The matching support system according to claim 1, Further storing a schedule of each of the providers' available working times; the difficulty level determination unit determines the difficulty level for each element of the request, a workload determination unit that calculates a workload for each difficulty level of the request; the first extraction unit generates the first extraction result for each of the difficulty levels; the second extraction unit generates the second extraction result for each of the difficulty levels; In the second extraction result for each level of difficulty, which can correspond to the amount of work for each level of difficulty, A third extraction result is generated in which the extracted combinations are described. Further provided is a third extraction unit Matching support system.

6. The matching support system according to claim 5, The provider candidates based on the third extraction result are displayed on the requester via a user interface. Recommendation section to present to customers, A matching support system further comprising:

7. The matching support system according to claim 5, The providers constituting the combination include a combination of providers belonging to different organizations. Included, Matching support system.

8. The matching support system according to claim 4, Accepting and storing evaluations from the provider regarding the requester who has received a request in the past A client evaluation registration unit; The provider provides a desired requester level, which is an evaluation threshold used to determine the desired requester. a requester level registration unit for receiving and storing the request; Further provided with The recommendation unit recommends the requester from among the candidate providers based on the second extraction result. Providers whose evaluation does not meet the desired requester level will not be presented to the requester. Matching support system.

9. The matching support system according to claim 6, Accepting and storing evaluations from the provider regarding the requester who has received a request in the past A client evaluation registration unit; The provider provides a desired requester level, which is an evaluation threshold used to determine the desired requester. a requester level registration unit for receiving and storing the request; Further provided with The recommendation unit recommends the requester from among the candidate providers based on the third extraction result. Providers whose evaluation does not meet the desired requester level will not be presented to the requester. Matching support system.

10. When a requester requests a service provider to provide a service, the requester and the service provider A method for supporting matching between providers, comprising: An information processing device having a processor and a storage device, basic information relating to each of the plurality of providers; Request information, which is information regarding the request received from the requester; A reliability level, which is information indicating the degree of reliability of each of the plurality of providers; and information indicating the expertise of each of the providers in the service; storing the determining the difficulty level of the request based on the request information; The provider having a higher reliability is extracted for the request having a higher degree of difficulty. A first extraction result listing candidates for service providers extracted from the basic information and the extracted results. generating a result; and The more difficult the request, the more specialized the provider for the service is extracted. The service provider candidates are extracted from the first extraction result so that the extracted result generating a second extraction result describing the A matching support method that implements the above.

11. The matching support method according to claim 10, The information processing device displays the provider candidates based on the second extraction result through a user interface. presenting the request to the requester via an interface; A matching support method that further implements the above.

12. The matching support method according to claim 10, The information processing device, further storing a schedule of available working times of each of the providers; A step of determining the difficulty level for each element of the request; Calculating the amount of work for each level of difficulty of the request; generating the first extraction result for each of the difficulty levels; generating the second extraction result for each of the difficulty levels; and In the second extraction result for each level of difficulty, which can correspond to the amount of work for each level of difficulty, A third extraction result is generated in which the extracted combinations are described. a step of forming a A matching support method that further implements the above.

13. The matching support method according to claim 12, The information processing device displays the provider candidates based on the third extraction result through a user interface. presenting the request to the requester via an interface; A matching support method that further implements the above.

14. The matching support method according to claim 11, The information processing device, Accepting and storing evaluations from the provider regarding the requester who has received a request in the past Step, The provider provides a desired requester level, which is an evaluation threshold used to determine the desired requester. receiving and storing steps; Among the candidate providers based on the second extraction result, the evaluation of the requester is a step of not presenting to the requester any provider who does not meet the level of a specialist; A matching support method that further implements the above.

15. The matching support method according to claim 13, The information processing device, Accepting and storing evaluations from the provider regarding the requester who has received a request in the past Step, The provider provides a desired requester level, which is an evaluation threshold used to determine the desired requester. receiving and storing steps; Among the candidate providers based on the third extraction result, the evaluation of the requester is a step of not presenting to the requester any provider who does not meet the level of a specialist; A matching support method that further implements the above.

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