JP2007213564A - Resource exploitation supporting method, information processor constituting network system for supporting resource exploitation, and computer program for supporting resource exploitation - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a network system for supporting the exploitation of resources to match the supply and demand between an enterprise and a management resource. <P>SOLUTION: In the network system including a server device and a plurality of terminal devices, each of the terminal devices creates both a quantitative data group, in which features of resources to become candidates for the supply and demand are quantized from plural viewpoints, and common data, in which featuring information for presenting the resource features to a user is expressed in a data format commonly recognized by the network system, and transmits the quantitative data group and the common data to the server device. The server device stores a supply/demand DB separately for each supply and demand of the resources with the quantitative data group and the common data coming from each terminal device, and compares the features expressed by the quantitative data group to discriminate the adaptability of the supply and the demand between the supplier and the demander of the resources. The server device can provide the terminal device of the demander with the common data of the supplier of the adaptability within a prescribed range can provide the terminal device of the supplier with the common data of the demander of the adaptability within a prescribed range. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a computer network technique for supporting resource utilization that enables the right person to be in the right place. The resources here include, for example, human resources, supplies, funds, information, intellectual property, and information on planned business projects related to business management. Among resources, those used for management are particularly called management resources. In addition, intellectual property, which is a kind of resource, is registered as a right, such as a patent right, trademark right, design right, utility model right, copyright, etc., as well as an invention, device, design, trademark, It refers to all intellectual creations prior to the acquisition of rights, such as know-how and research data. For example, literary works are also intellectual property. In this specification, this intellectual property is abbreviated as “IP” unless it is used as a keyword. Further, among IPs, those that can be managed as an independent entity such as purchase, transfer, license-in, and license-out are referred to as “IP tools”.

  Management resources, especially IP tools, play a major role in business strategy. In addition to creating an intellectual property tool independently by an organization or an individual, what is often created by another organization or individual is acquired by a transaction. However, in the past, IP tool transactions could only be realized with relative transactions with familiar partners. In other words, in the past, individual negotiations through the section in charge of licensing in a company or the like was the main method for distributing intellectual property tools. An example of an individual negotiation was to conclude a non-disclosure agreement and then disclose confidential information and present transaction terms during the sample trial period. In such a mode of negotiation, the cost and time for the search that the business partner bears are usually enormous. Therefore, there was a tendency to hinder the smooth distribution and utilization of IP tools.

  In order to activate the distribution of intellectual property tools, various systems have been proposed in which a website is provided on the Internet, and through which the intellectual property tools are bought and sold or licenses are mediated. For example, JP 2004-78525 A, JP 2004-78524 A, JP 2004-62669 A, JP 2003-337892 A, JP 2003-331160 A, and JP 2003-331159 A. Publishes the contents of the intellectual property rights to be sold and the conditions for selling them (there is a device for calculating the evaluation amount, etc.) on the Web site server, and accepts bid applications that are determined to be legitimate. An intellectual property right trading system has been introduced.

  Japanese Patent Laid-Open No. 2002-99776 discloses that in order to promote the trading of rights related to intellectual property, it becomes a more favorable condition for those who have applied for transactions earlier than those who have applied for transactions later. In addition, the transaction provider sets up multiple transaction conditions using the transaction provision device, publishes the contents of the rights and the transaction conditions to the server, and the transaction recipient selects the transaction conditions and applies for the transaction. The right trading method is introduced.

  Furthermore, in Japanese Patent Laid-Open No. 2003-331154, in order to support technology transfer for buying and selling intellectual property and licensing, a technical overview, a person involved in technology transfer (seller, buyer, broker), request contents, Search for the most appropriate combination of registered contents by registering specialized fields, etc., or perform matching by assigning grades according to the degree of matching between terms used in the registered contents. A technology transfer support system that provides information to those involved in technology transfer is introduced.

JP2004-78525 JP2004-78524 JP 2004-62669 A JP 2003-337892 A JP 2003-331160 A JP 2003-331159 A JP 2003-331154 A JP2002-99776

  Such a conventional system is very convenient in reducing the cost for searching for a side (supplier) that provides an intellectual property tool and a side that receives the tool (demand source), for example. . However, in reality, the market distribution of intellectual property tools is not necessarily activated. The reason is considered to be as follows.

(1) Business strategy and intellectual property strategy are not linked.
Roughly, “strategy” is a basic policy to guide surrounding changes in a direction that is convenient to you, but IP strategy that is far from business strategy is realistic because IP tools are not used. There is no. Conversely, a business strategy that does not have an IP strategy perspective is dangerous because it is likely to be influenced by the IP tools of others. In other words, the intellectual property strategy cannot be determined without the perspective of how to use the intellectual property tool for what kind of business, as with real estate. However, in many organizations, the IP strategy, that is, the guidelines for utilizing IP, is not always clear.

(2) The business strategy using IP tools is top secret.
For example, disclosure of intellectual property strategies by technology development companies leads to disclosure of trade secrets. For example, information on what IP tools your company needs or what IP tools you do not need is a good way to look into your management policies in advance from other companies. . Many companies generally hide their IP strategy from the outside. Moreover, it is generally impossible to form an IP tool in the open market and form a price based on the market principle. Transactions must always be relative in a confidential relationship.

(3) Insufficient utilization of intellectual property intellectual property tools.
Some unused IP tools cannot be commercialized only by the organization that owns them. However, unexpected values may be created by changing the combination of IP tools, the combination of IP tools and business plans, or the combination of IP tools and other management resources with existing ones. is there. However, conventionally, there is no right place for finding the optimal solution for matching management strategies with intellectual property tools and other management resources.

(4) Needs matching is a unique problem.
Information within the organization that created the IP tool, and industry information are usually best known by those within the organization. Therefore, it is impossible to match the needs of the demand source and the supply source in the “mass” transaction of the intellectual property tool in the intellectual property secondary market.
(5) Recombination of resources other than intellectual property tools is difficult.
Technology transfer to other companies in the industry and licenses for intellectual property tools generally result in weakening the competitiveness of the company. The exchange of human resources is a secret issue. In order to solve such a problem, it is necessary to break down existing management resources into individual elements and optimize them, but this requires considerable energy.

  Regardless of the intellectual property tool, the market for resources that can be distributed is generally established by the relationship between the push of the supply source and the pull of the demand source. Pushing is often done from a strategic perspective of the business. For example, there is a tendency to be triggered by strategic licensing out of resources, inventory, division of departments, and the like. On the other hand, there are many negative pulls such as conflict avoidance, restraint against competitors, and business restructuring. For the above-mentioned reasons described for the IP tool, conventionally, the pressure of push and pull has not been applied to the inside of the organization.

However, push and pull are inevitable for revitalizing the business involved by effective use of resources. Creation of push and pull is necessary to dominate the market and connect the business and management strategy to success. It is. What needs to be done in order to create push and pull is, for example, to incorporate an information preparation mechanism for business strategy, particularly an information preparation mechanism for risk hedging by push. Also, what needs to be done to create a pull is, for example, when there is a resource that you want to supply or can supply, that other companies will tailor that resource to “what you want” and become a pillar of your business strategy. It is to establish a model to procure resources from outside.
At present, there is no system for unified management of resource transactions from a strategic perspective within a company. This is because the information is enormous and complicated, and there is not enough data to make an effective decision only with in-company information.

  The main object of the present invention is to propose a new resource utilization support mechanism that enables the right person to find the right solution for finding the optimal solution for matching business strategy and management resources, for example.

  The present invention relates to a resource utilization support method that is connected through a network and executed by a plurality of devices, an information processing device for a network system that is suitable for implementing this method, and a computer that uses such an information processing device. A computer program for realizing the above is provided.

The resource utilization support method provided by the present invention is a method that is executed by a server device and a plurality of user devices respectively connected via a network, and includes the following steps as the execution procedure: .
(1-1) A first user device operated by a user who can be a demand source of a resource to be utilized and a second user device operated by a user who can be a source of the resource respectively have the characteristics of the resource. Quantifying based on a plurality of types of evaluation rules with different viewpoints to convert the data into a quantified data group in a data format that can be recognized by the server device, and to transmit feature information for transmitting the resource to other users Supply / demand ID (ID is an identification) for converting the quantitative data group and the common data into a data format that can be recognized by the server device and other user devices, and identifying the resource demand source or the supply source, respectively. A step of transmitting to the server device together with an abbreviation of information (hereinafter the same).
(1-2) The server device stores the quantitative data group and the common data received from the first user device and the second user device in a predetermined storage device in association with the supply and demand ID, respectively. By comparing each of the characteristics represented by the quantitative data group that is represented for each set of the demand source and the supply source specified by the supply and demand ID, the degree of conformity between the demand and supply of the resource is determined, The first user device can be provided with common data of the supplier whose degree of fitness falls within a predetermined range, while the second user device can be provided with common data of a demand source whose degree of fitness falls within the predetermined range. Stage to do.

  In contrast to the conventional technology, particularly the technology related to technology transfer support described in Japanese Patent Application Laid-Open No. 2003-331154, in the technology of the present invention, a quantitative data group in which the feature of the resource is recognized by the server device, that is, a plurality of quantitative data Compared with the conventional technology that performs matching based on the score according to the degree of matching between terms, the server device compares the demand source and the supply source with the server device. Relevance can be greatly increased. In addition to the conversion to the quantitative data group, the feature information about the resource is converted into common data that can be recognized by other user devices. Therefore, since the common data of the demand source is provided, the user can not only perform matching by information processing as in the prior art, but also the user can confirm the accuracy of the fitness determination in an analog manner.

  In an embodiment of the utilization support method, each of the first device and the second user device transmits an indirect ID for indirectly identifying an attribute of a user who operates the device to the server device. On the other hand, the server device stores the indirect ID received from each user device in the storage device in association with the common data from the user device, and stores the common data of the supply source in the first user device. When providing, it is possible to provide the indirect ID of the supply source and conceal the indirect ID of the other demand source. On the other hand, when providing the second user device with the common data of the demand source, The indirect ID can be provided and the indirect IDs of other suppliers are concealed. As a result, the other attribute can be indirectly grasped between the demand source and the supply source, while the existence of the demand sources or the supply sources is concealed. Resource supply and demand information can be acquired.

  From the viewpoint of the convenience of the demand source, the server device acquires at least one of evaluation information representing a third party evaluation result for the resource and support information representing an example of utilization of the resource. The evaluation information or the support information is stored in the storage device in association with the supply source general data, and at the time of providing the general data, at least one of the evaluation information and the support information can be provided together. . Thereby, the objectivity with respect to the resource to be supplied is ensured, and it is possible to give information that is effective for transaction determination to the user of the demand source.

The user, whether it is a demand source or a supply source, generally performs a further information search and makes a transaction judgment after information is transmitted from the server device. Correspondingly, in the present invention, the server device stores a keyword DB storing a plurality of keywords related to resource utilization, and the ID of a plurality of associative keywords associated with the keyword for each keyword. An association table associated with each appearance frequency in the data is prepared. When a search request with a search keyword candidate is received from the first user device or the second user device, it is an associative keyword associated with a keyword that matches the search keyword candidate, and its appearance frequency is predetermined. A number of associative keywords belonging to a range are extracted from the keyword DB based on the record information of the relevance table, and the extracted associative keywords can be provided as potential search keywords to the user device that is the source of the search request. To do.
From the viewpoint of making the record information of the relevance table more effective, each time the server device detects that any of the associative keywords provided to the source user device is adopted as a search keyword. In addition, information indicating the use degree of the associative keyword is recorded in an area of the relevance table associated with the ID of the associative keyword. Further, in order to give more “awareness” to the user, the server device, from the record information of the association table, some associative keywords with a relatively high appearance frequency, the appearance frequency is relatively low Of the several associative keywords and the filing frequency, at least one of the associative keywords within the range specified by the user apparatus of the transmission source may be specified, and the specified associative keywords may be extracted.

The information processing apparatus of the present invention is a first information processing apparatus that operates as the first user apparatus or the second user apparatus described above, and a second information processing apparatus that operates as the server apparatus described above.
The first information processing apparatus is an apparatus that constitutes a network system for resource utilization support together with a server apparatus connected via a network, and includes the following components.
(2-1) The server device can be recognized by the user operating the device by quantifying the characteristics of the resource to be supplied or supplied based on a plurality of types of evaluation rules with different viewpoints. First data conversion means for converting into a quantitative data group in a data format.
(2-2) Second data conversion means for converting feature information for allowing other users to recognize the feature of the resource into general data in a data format that can be recognized by the server device and other information processing devices.
(2-3) The quantitative data group and the common data are transmitted to the server device together with a supply and demand ID for identifying the demand source or the supply source of the resource, and the features represented by the quantitative data group are compared. Of the supply source information including the common data of the supply source, or the demand source information including the common data of the demand source, from the server device that is performed for each set of the demand source and the supply source specified by the supply and demand ID Communication means for receiving either.
(2-4) Output control means for enabling supply source information or demand source information received by the communication means to be presented to the user through a predetermined output device.

  In order to convey surprising feature information to other users, for each keyword, information that can be associated with the keyword and selected by a person other than the user, or an action of a person other than the user The information processing apparatus further includes an associative support DB that stores serendipity information generated due to the information, and the second data generation unit converts the serendipity information corresponding to the keyword included in the feature information into the association The extracted serendipity information may be included in the feature information and converted into the common data. Further, the first data generation means extracts serendipity information corresponding to a keyword included in the resource feature from the association support DB, and includes the extracted serendipity information in the resource feature in the quantitative data group. You may make it convert.

The second information processing apparatus is an information processing apparatus that constitutes a network system for resource utilization support together with a plurality of user apparatuses, and includes the following components.
(3-1) Quantitative data quantitatively converted from each user device into a data format that can be recognized by the own device based on a plurality of types of evaluation rules that have different viewpoints of the resources to be supplied or supplied. Group, and general data in which feature information for allowing other user devices to recognize the resource is converted into a data format recognizable by the own device and the other user device, respectively, as a demand source or a supply source of the resource. Receiving means for receiving together with a supply and demand ID for identification.
(3-2) Supply / demand DB that stores the received quantitative data group and the common data from each user device in association with the supply / demand ID.
(3-3) By comparing the features of the quantitative data group accumulated in the supply and demand DB for each set of the demand source and the supply source specified by the supply and demand ID, the degree of fitness of supply and demand is determined, and the demand source It is possible to provide supply source information including common data of a supplier whose fitness is within a predetermined range to the user device according to the above, while the user device of the supplier has a demand source whose fitness is within a predetermined range. Supply and demand management means that enables supply of demand source information including common data.

  From the standpoint of enabling management support for management resources in a closed environment, the supply and demand management means can provide other demand sources when providing the supply source data when there are a plurality of demand sources of the resources. On the other hand, when there are a plurality of supply sources of the resource, the existence of other supply sources is concealed when providing common data of the demand source.

The second information processing apparatus can also be configured to include the following components.
(3-4) A keyword DB storing a plurality of keywords together with an ID for identifying each keyword.
(3-5) One of the keywords stored in the keyword DB is defined as a title keyword, and is stored in the keyword DB among a plurality of keywords extracted from the source document data, excluding the title keyword. Keyword management means for defining the same keyword as the associated keyword as an associated keyword and deriving the appearance frequency for each associated keyword in the source document data.
(3-6) The title keyword and the ID of each derived associative keyword are extracted from the keyword DB, respectively, and the ID of each associative keyword and the appearance frequency derived for each associative keyword are determined as the title keyword. Table management means for generating a relevance table representing the relevance between the title keyword and each associative keyword, or updating the recorded information thereof.
(3-7) Keyword candidate receiving means for receiving input of search keyword candidates for searching for information related to the resource utilization support.
(3-8) It is checked whether or not there is a relevance table of title keywords that matches the search keyword candidate received by the keyword candidate receiving means, and if it exists, a plurality of IDs recorded in the relevancy table are stored. Search means for extracting an associative keyword corresponding to each ID from the keyword DB and providing the extracted associative keyword as a potential search keyword that can be adopted as a search keyword to a sender of the search keyword candidate.

  The keyword management means measures, for example, the appearance frequency of a plurality of extracted keywords extracted from the title area in the source document data in the title area, and the same keywords as these extracted keywords are stored in the keyword DB. A search is made as to whether the keyword is stored, and if it is stored, the same keyword as the extracted keyword having the highest appearance frequency is determined as the title keyword.

  Detecting means for detecting that any one of the associative keywords provided to the sender is adopted as a search keyword, and the table managing means associates the number of detections by the detecting means with the ID of the associated keyword. You may comprise so that it may record cumulatively in the said relationship table.

  In order to give a user who is a searcher a lot of “awareness” about resource utilization, the search means is configured to obtain IDs of some associative keywords having a relatively high appearance frequency from the recorded information of the relevance table, IDs of some associative keywords with a relatively low appearance frequency, IDs of some associative keywords with a relatively high cumulative number of detection times, and IDs of some associative keywords with a relatively low cumulative value , Identifying at least one of the IDs of the associative keywords within the range specified by the sender from the appearance frequency or the cumulative value, and extracting the associative keywords corresponding to the specified IDs from the keyword DB Also good.

A first computer program according to the present invention is a computer program for causing a computer to operate as a user device that constitutes a network system for resource utilization support together with a server device connected through a network.
Quantitative data group in a data format that can be recognized by the server device by the user operating the device quantifying the characteristics of the resource to be supplied or supplied based on a plurality of types of evaluation rules with different viewpoints. First data conversion means for converting to a second data conversion for converting feature information for allowing other users to recognize the resource into general data in a data format recognizable by the server device and other information processing devices Means, the quantitative data group and the common data are transmitted to the server device together with a supply and demand ID for identifying a demand source or a supply source of the resource, respectively, and a comparison between the features represented by the quantitative data group is performed. From the server device performed for each set of demand source and supply source specified by the ID, supply source information including the common data of the supply source, or Communication means for receiving any of the demand source information including the common data of the key point, and output for enabling supply source information or demand source information received by the communication means to be presented to the user through a predetermined output device A computer program for resource utilization that functions as a control means.

  A second computer program of the present invention is a computer program for causing a computer having a storage device to operate as a server device constituting a network system for supporting resource utilization together with a plurality of user devices connectable through a network. In addition, the supply / demand DB is constructed in the storage device, and the computer recognizes the computer from each user device based on a plurality of types of evaluation rules whose characteristics of resources to be demanded or supplied are different from each other. Quantitative data group quantitatively converted into a possible data format, and feature information for causing other user devices to recognize the resource is converted into a data format that can be recognized by the own device and other user devices The data is shared with the supply and demand ID for identifying the demand source or the supply source of the resource, respectively. Receiving means for receiving, DB management means for storing the received quantitative data group from each user device and the common data in association with the supply / demand ID, and storing it in the supply / demand DB, characteristics of the quantitative data group stored in the supply / demand DB By comparing each pair for each of the demand source and the supply source specified by the supply / demand ID, the suitability of the demand / supply is determined, and the user device related to the demand source has a supply source whose suitability falls within a predetermined range. Supply and demand management means that makes it possible to provide supply source information including common data, and on the other hand, can provide demand source information including common data of a demand source having a degree of conformity to a user device related to the supply source. This is a computer program for resource utilization support to function.

According to the present invention, information on a resource supply source that meets the demand is transmitted to a user who can be a resource demand source. In other words, pull can be created. On the other hand, information on the demand source of the resource suitable for the supply is transmitted to the user who can be the resource supply source. In other words, push can be created. As a result, it is possible to obtain a specific effect that it is possible to select and concentrate resources at the demand source and the supply source.
In addition, since the user device related to the demand source and the user device related to the supply source are provided with information indicating the contents of the resource as common data, it is determined whether the user of the supply source is a resource that meets the demand. Can provide information for easily judging whether the contents of the resource are attractive to itself. When the resource is an intellectual property tool, it is very difficult to correctly recognize the feature, so the above-described effect of the present invention becomes more remarkable.

Hereinafter, embodiments of the present invention will be described.
<First Embodiment>
[Overall configuration diagram]
FIG. 1 shows an example of an overall configuration diagram of a network system to which the present invention is applied. In the present embodiment, an example is shown in which the resource to be utilized support is a management resource used for business management. The network system is configured by connecting a plurality of terminal devices 1 each operating as a user device and a server device 2 installed in an organization that performs system management, for example, via a wide area network WN such as the Internet. . The terminal device 1 is installed in a company, a university, an individual business operator, etc. (hereinafter referred to as “in-house” for convenience). In the case where the wide area network WN is the Internet, the server device 2 can be implemented as a single or a distributed processing Web system applying grid computing or the like. Further, the server device 2 can also have the function of the terminal device 1.

  The wide area network WN includes a public institution system 3 such as the JPO Digital Library that provides information on intellectual property tools, a data bank 4 installed in a private information provider, management, intellectual property, legal experts, etc. A third-party operation terminal 5, an expert system 6 and the like installed in the third-party organization to which the user belongs are connected, and various types of information useful for utilizing the management resources are appropriately stored in the terminal device 1 or the server device 2. It can be obtained at.

In this network system, each of the plurality of terminal devices 1 manages management resources based on their own circumstances. If the result is that the current management resources are not excessive or insufficient for the company in carrying out the current business or the business to be carried out (hereinafter referred to as “target business”), the terminal device Only one process is enough. On the other hand, if there is an excess or deficiency in the current management resources for executing the target business and you want to trade with the outside for the excess or deficiency, supply and demand information, that is, the demand for the deficient resources. For the surplus resources, the server apparatus 2 collects supply information.
The server device 2 accumulates the aggregated supply and demand information from each terminal device 1 for each supply and demand, performs suitability determination for each pair of supply and demand, and sends information (supply) from the supply source to the terminal device 1 that is the demand source. Source information) and various kinds of information about the resource can be provided in a state where the existence of other demand sources is concealed. Further, it is possible to provide the terminal device 1 serving as a supplier with information from the demand source (demand source information) and value-added information about the resource in a state where the existence of other suppliers is concealed. First, configuration examples of the terminal device 1 and the server device 2 that enable such an operation will be described.

[Terminal device]
The terminal device 1 is a computer (information processing device) that is operated by a terminal computer program. That is, the terminal device 1 can be realized by a computer having a storage device such as a hard disk, an input device such as a keyboard / mouse, and an output device such as a display executing the terminal computer program of the present invention. The terminal computer program is distributed in a form that can be downloaded from the server device 2 by being recorded in a computer-readable form on a recording medium such as a disk or through the wide area network WN.

  In the present embodiment, as shown in FIG. 2, the management strategy DB 11 is constructed in the storage device by the terminal computer program, and the computer is connected to the main control unit 10, the communication control unit 12, the input control unit 13, and the output control. Section 14, management resource management section 15, relevance data management section 16, and general data management section 17.

  The management strategy DB 11 is categorized and stored with a lot of support information for enabling the right place for management resources by push creation and pull creation under the control of the management resource management unit 15. In this embodiment, such support information is classified and stored in five types of DBs: an internal resource DB 111, an external resource DB 112, an associative support DB 113, an option DB 114, and a rule file 115.

  The internal resource DB 111 stores management information of management resources owned by the company. Management resources to manage include, for example, intangible assets used in-house such as know-how and skills, intellectual property tools that can be used in and outside the company, human resources, supplies, funds, customer information, strategic information, business projects under consideration, etc. Information. Management information includes financial information that may or may arise from the use of these management resources. The management information is identified from information of other management resources by a resource ID for uniquely identifying the management resource to be managed in the system. The information stored in the internal resource DB 111 is extracted by ID search or keyword search according to the purpose of support for the operating user, and information processing using the extracted information is performed. Make analysis possible.

  The external resource DB 112 is owned by an organization or individual other than its own company (hereinafter referred to as “other company” for convenience), and information on management resources that the company wishes to own or is interested in, for each such management resource. Objective evaluation information, external support information for business, and various statistical information are classified and stored for each field and business. Each field or business is distinguished by an ID for uniquely identifying it in the system, and corresponding information can be extracted by a search based on keywords in these IDs or various information. The information stored in the external resource DB 112 is extracted by ID search or keyword search according to the purpose of support for the operating user, and by performing information processing using the extracted information, not only the company but also other companies It is possible to make a judgment on the relative strength analysis and the demand or supply of management resources for the target business.

The association support DB 113 stores serendipity information for supporting user association. The serendipity information here is such information that the user has not noticed, but has been searching for, and makes the user aware of it by chance. The association support DB 113 is a method of matching information in view of the fact that “knowing knowledge” expressed by humans has only a limited meaning, but its range is ambiguous and difficult to convey correctly to other humans. It is provided from the viewpoint of providing unexpected information and providing at least the level of information desired by the user from the terminal device 1.
In the present embodiment, for example, electronic data of a synonym dictionary, an antonym dictionary, and dictionaries registered by many users are held as an example of serendipity information. Then, a synonym, an antonym, and a registered word associated with the word or phrase specified by the user are included in the later-described common data or output together with the common data. For example, when the user designates the word “personal computer”, unexpected information such as entertainment, machine, waste, distribution,... Beyond thesaurus information can be output as serendipity information. In addition, when generating feature data of management resources, which will be described later, serendipity information is included in one of the feature data.

  The option DB 114 includes a security information file, a risk factor file, a pseudo plan file, a screen layout file, a management resource classification result file, a decision tool file, a human resource file, and a risk factor file as required by the user. Information to be used selectively is stored.

  The security information file contains the operation authority level for user authentication and company attributes (for each company section, for example, each management team, planning department, intellectual property department, sales department, research department). Information with high security such as an indirect ID that indirectly represents an organization name or personal name, IR information, etc., and an indirect ID of each department of another company received from the server device 1 is stored. The indirect ID is used to prevent the company's attributes from being immediately recognized from the ID, and is used to convey the minimum information necessary for the transaction only to the party that can meet the demand and supply. .

  The risk factor file contains the risks determined by the type of target business, for example, the estimated amount of additional costs required when there is no IP tool, the number of other company patents, the number of company patents, the relative ability value of other company patents and company patents, The license-out fee that the company can accept, as well as the license-in fee, etc., are stored as risk factors in utilizing the management resources. This information is taken into account when determining whether there is a supply and demand for IP tools.

  The pseudo-plan file includes multiple pseudo-plans for the target business, data for simulating each pseudo-plan, statistical data for each existing business, market data related to the business, information on alliances / related / competitions, supply chain information, etc. Are stored in association with the business ID. This information is also taken into account when determining whether there is supply and demand for management resources.

  The screen layout file also stores a plurality of interface screens to be displayed on the display of the terminal device 1, layout data of each interface screen, and the like. In addition to the information display area that varies depending on the operation authority level, the interface screen also has a common area for displaying information for supporting the communication between the involved departments and the command system. Through the display of this common area, Uniform information for the entire organization can be shared by users of all authority levels.

  In the classification result file, related information files classified once for each management resource accumulated in the internal resource DB 111 and the external resource DB 112 are stored. For example, a plurality of files such as an intellectual property tool file, a financial information file, a cost information file, a marketing information file, a decision tool file, and a human resource file are stored in association with each other. Information of each file is appropriately displayed visually through an interface screen displayed on the display, for example, a classification menu screen.

  FIG. 3 shows an example of a certain classification menu screen displayed on the display which is one of the output devices under the control of the management resource management unit 15, the output control unit 14 and the main control unit 10. In the figure, the “IP” item is the IP tool file storing the IP tool, the “Finance” item is the financial information file storing the financial information of the business associated with each IP tool, and the “Cost” The item is a cost information file that stores cost information related to the maintenance of each intellectual property tool, the “Marketing” item is a marketing information file that stores marketing information about the business related to the IP tool, and the “Decision” item is knowledge A decision support file that stores tools that support decision making when utilizing the tool, and the item “Human Resources” is a human resource information file that stores human resource information about the business that involves the IP tool. Each file is associated with the ID of each IP tool in the IP tool file as a key. That. 4A to 4C and FIGS. 5A to 5C are display screens of content examples of files that are switched and displayed when the user clicks the “click” image of each item in FIG. An example is shown.

  FIG. 4A shows a display screen example of the contents of the intellectual property tool file. In other words, for each patent that is a part of the intellectual property tool that the company owns, it is linked with the category name that briefly expresses the content, the registration number, and information that indicates whether or not the business that uses it is implemented in-house It shows how the index is stored. The linkage index is an evaluation value that is quantified based on a comparison between feature information representing the features of an IP tool unit linked to a business and predetermined evaluation standard data. For example, a relative value when the perfect score is 100 It is represented by This interlocking index can be one of quantitative data groups described later. That is, if the interlocking index is “80”, it can be obtained as one of quantitative data by multiplying the numerical value by the weighting coefficient for other management resources found by the external resource DB 112.

  Referring to FIG. 4B, the decision-making tool file includes a decision tree data for a business related to any of the patents shown in FIG. 4A, that is, for implementing the patented invention. Is stored. The decision tree is used, for example, when calculating the above-described interlocking index. In other words, it is used for weighting such as lowering the index unless it is implemented in-house.

  Referring to FIG. 4C, the human resource file stores the connection of the internal section of the project and the connection of the external system or section related to the intellectual property tool file. In other words, information on secured human resources is accumulated. Thereby, since the excess or deficiency of human resources, which is one of management resources, is displayed visually, the user can easily determine whether the right person in the right place is possible.

  Referring to FIG. 5A, the marketing information file includes an intellectual property tool (patent) intellectual property map stored in the intellectual property tool file, a marketing segment map, or a positioning map obtained by merging them. Data to be expressed with a three-dimensional structure is stored. That is, a plurality of competing companies and their own management resources are expressed numerically on a three-dimensional coordinate axis from three viewpoints of concentration (resource), technology orientation, and market orientation. On the next interface screen that is hierarchized, the positioning can be evaluated with a plurality of matrices such as technical characteristics, and further on the next interface screen, evaluation criteria. In addition, the screen structure conforms to micro analysis (such as SWOT), each company's business plan, market share, and organizational structure. If necessary, macro environment information, that is, intellectual property macro environment information and economic macro environment information is used. These map data are referred to, for example, when selecting a target business and determining the supply and demand of various resources by the business. This marketing information allows the user to visually determine the possibility of the business.

Referring to FIG. 5B, financial data for several years is accumulated in the financial information file for the business associated with the intellectual property tool file. This is referred to, for example, when determining whether to continue / stop the business, whether to develop a new business, or the like. In the cost file of FIG. 5C, the cost of the intellectual property tool associated with the intellectual property tool file, for example, the right acquisition cost, the maintenance cost, and the like are accumulated. This is referred to, for example, in determining whether it is better to supply an intellectual property tool.
By performing information processing using the information in each file according to the purpose, analysis of the current strength of the company for each management resource, etc., and selection of candidates for the target business and management associated therewith are performed. Make it easier to determine resource supply and demand.

  The rule file 115 stores a plurality of evaluation rules for strategically evaluating and analyzing the characteristics of the management resources of the company / other companies. In this embodiment, qualitative evaluation rules, quantitative evaluation rules, correspondence rules, and relevance level evaluation rules are stored, and these are appropriately combined depending on the usage, thereby quantifying the characteristics of management resources from a plurality of different viewpoints. Be able to

  The qualitative evaluation rule is a rule that defines a method and a parameter for performing a relative evaluation for each management resource or each business related to management resources, that is, ranking evaluation by scoring. The quantitative evaluation rule is a rule that defines an execution procedure and parameters of an evaluation formula for performing quantitative evaluation based on one management resource or a combination of a plurality of management resources, that is, price calculation. Each of the qualitative evaluation rule and the quantitative evaluation rule is associated with a purpose ID representing an evaluation purpose and reference data to be referred to at the time of evaluation. When evaluating for each business or each management resource, it is also associated with the business ID and management resource ID.

  For example, when the management resource is an intellectual property tool, the quantitative evaluation rule has the contents shown in FIG. In the case of the example of FIG. 6, data corresponding to the evaluation purpose of the intellectual property tool (IP) distinguished by the subscript (n or the like) is set in the purpose ID column of the quantitative evaluation rule R101. For example, “IPnH” is “IPnH” if the IP tool identified by “IPn” is owned by the company, “IPnS” if the IP tool is “transferred”, and “IPnS” if “Purchase”. The purpose ID is set such as “IPnB”, “IPnL1” for “license out”, and “IPnL2” for “license-in”.

  In the field of quantitative evaluation rule in the field associated with each purpose ID, for example, an evaluation approach method, basis information used for evaluation, execution procedure, use rule of coefficient data to be used, and the like are set. As the basis information to be used, for example, the address of one or more types of information stored in the management strategy DB 11 is defined (ad ** 10 to 52 in FIG. 6). Approach approaches include, for example, a market approach based on market value (m1 to 4 in FIG. 6), an income approach for calculating earnings (discount cash flow: DCF method or its improved method, and other evaluation methods: FIG. 6). Medium, i1-8), royalty approach based on the amount of the fee (r1 to r19 in FIG. 6), etc. are defined. The execution procedure is the order of actual evaluation. For example, after business evaluation, evaluation is performed in the order of products, sales points, and intellectual property tools. Each of them can be selected according to in-house circumstances (p12 to p61). Different coefficient data to be used are prepared depending on the evaluation purpose (d211 to d601 in FIG. 6).

Corresponding to each quantitative evaluation rule, statistical data of similar market prices in the market approach, parameters such as valuation formulas and risk factors by sector for the income approach, and state-owned patent royalty rates and factors by sector for the loyalty approach Are stored in association with respective purpose IDs. In FIG. 6, “i1101”, “i1102”, “m1105”, “L11110”, and “L11112” shown in the reference data column are addresses of files in which the reference data is stored.
For management resources other than intellectual property tools, or combinations thereof, a quantitative rule having items determined in advance in consideration of strategic elements is prepared in the same manner as in the case of FIG.

  The correspondence rule is a rule for associating and quantifying management contents and affiliation classifications recognizable in the apparatus, such as a field to which a business belongs and its detailed classification, types of management resources and identification symbols thereof, and the like. FIG. 7 is a diagram showing an example of the contents of this correspondence rule. FIG. 7A shows the correspondence between the field and the detailed classification. As an example, a rule R201 corresponding to the international patent classification table is stored. FIG. 7B shows a rule R301 in which the type of management resource is associated with each affiliation category. In addition, design classification, international trademark classification, and the like can also be used as one of the corresponding rules. Of these correspondence tables R201 and R301, the details of the right item column are listed in detail in the dialog window of the interface screen, and the user simply selects using an input device to identify the corresponding item. Data is input. Corresponding rules are also used when generating relevance data. The relevance level evaluation rule is a rule for expressing the degree of relevance between a target business to be utilized and management resources. This will be described later.

Returning to FIG. 2, other functional blocks in the terminal device 1 will be described.
The communication control unit 12 performs bidirectional communication with the server device 2 in accordance with parameters and protocols recorded in a memory area (not shown), and direct communication with other devices or systems connected to the wide area network WN. Enable. The communication control unit 12 also manages a firewall existing between the wide area network WN and prevents information managed by the own device from being stolen by an external device.

  The input control unit 13 includes an input device operated by a user, in-house information storage means (not shown), or a server device 2 connected to the wide area network WN, another terminal device 1, a public institution system 3, a data bank 4, a first Input of information from the three-party terminal 5 and the expert system 6 is received, and control for transmitting these information to the management resource management unit 15 is performed. The input control unit 13 performs user authentication when the user performs an initial operation. That is, the interface screen for authentication is displayed on the display, and when the authority information is input from the user according to this, the authority information is compared with the authority information stored in the option DB 114. The interface screen of the hierarchy corresponding to the operation authority level is specified from the option DB 114, and the interface screen is displayed on the display. On the interface screen, a support purpose menu, that is, an item associated with the above-described purpose ID on a one-to-one basis is displayed as a menu. The input control unit 13 also translates the content of the instruction input through the input device by displaying the interface screen, and transmits the translation result to each functional block including the main control unit 10. For example, when a specific item is selected from the menu of the interface screen displayed on the display, the contents associated with the item are set according to a predetermined rule for each function block (the main control shown in FIG. 2). Section 10, management resource management section 15, relevance data management section 16, and general data management section 17). Then, the converted data is transmitted to the corresponding functional block. The same applies to contents selected through display of other interface screens. As a result, the business type, purpose ID, correlation condition and other data input by the user are correctly transmitted to the corresponding functional block.

  The output control unit 14 performs various representations by performing selection of information to be output to a display, editing, information mapping, image processing, and other output control in accordance with an instruction selected by the user in accordance with an instruction from the user. Produce form. The screens shown in FIGS. 3 to 5 are obtained as a result of information selection by the output control unit 14. The output control unit 14 also controls the timing for displaying information on the display.

  The management resource management unit 15 performs processing related to the push / pull creation support of the company's management resources. Specifically, it includes a DB manager 151, an information search / analysis engine 152, and a management simulator 153 having a value evaluation function for business or management resources as auxiliary modules, and information on management resources owned by the company and other companies. In addition to managing, it performs processing for concept creation, business strategy planning, determination of necessity of supply and demand, and other decision support based on information on these management resources.

  The DB manager 151 selects the information received by the input control unit 13 and stores it in the corresponding DB in the management strategy DB 11 so that each information can be read out appropriately. The search / analysis engine 152 searches for information from, for example, the management strategy DB 11 and an external information providing site by inputting an arbitrary keyword, and performs various analyzes based on the searched information. The analysis is performed, for example, on the strategies of competing organizations, the contents of competing management resources, the current status of management resource transactions, and risk factors.

  The management simulator 153 is stored in the management strategy DB 11 in response to the simulation purpose input from the user through the menu selection on the interface screen displayed on the display and the reception of necessary conditions or parameters (various variables). It is possible to simulate the change of events for business management by reading various information and performing information processing combining the read information with the input conditions or parameters. When the simulation is performed qualitatively, a qualitative evaluation rule stored in the rule file 115 is used. When simulating quantitatively, a quantitative evaluation rule is used. That is, the qualitative evaluation rule / quantitative evaluation rule associated with the purpose ID representing the purpose specified from the rule file 115 and the current management resource information stored in the management strategy DB 11 are read, and the management resource is stored in each rule. By applying this information, it is possible to quantify, for example, the prediction of future risk hedges in the business, the excess or deficiency of the company's management resources, and how much economic value is created by the management resources that meet the specified conditions. be able to.

  Risk hedging is the elimination of uncertainties or minimizing damages, and the forecast is derived from, for example, the expected profit margin when the management resources held in-house are transferred or licensed to other companies, and the fluctuation of the expected profit margin. This is a process of identifying the risk of the business to be applied and calculating the limit point that the profit from the transfer incorporating the identified risk always exceeds the profit from the management and use of management resources.

The excess or deficiency of the company's management resources is a so-called discrimination of supply and demand of management resources in the company. For example, it is a process of outputting a result that a certain management resource is insufficient, a certain management resource is not necessarily required, or a certain management resource is not required at all in executing the target business. When management resources are insufficient, it is determined as “demand”, and when management resources are not required, it is determined as “supply”.
A management resource that satisfies a specified condition is, for example, a management resource when all necessary IP tools and funds are replenished, or a management resource when some necessary items are not replenished, and its economic value. According to the management resource, for example, a process of outputting a result that an excess profit of m yen or loss occurs after n years, for example.

  The management simulator 153 also calculates the future growth rate based on the company's past and current financial information, and based on this, the resources (amount of money) used to acquire the intellectual property tool among the management resources. Conversion), the funds necessary to maintain the IP tool, the profits generated by the current IP tool, the extent to which the IP tool can be transferred or licensed, and the management resources including the IP tool after the transaction is concluded The range of profits to be obtained is also predicted as one of the evaluations.

The management simulator 153 selects, from the option DB 114, a pseudo plan based on the management resource directly input by the user or designated by the user, instead of the management resource information already accumulated in the management strategy DB 11. The future business development of the pseudo plan may be simulated based on the quantitative evaluation rules for the business and management resources with similar selected pseudo plans. The simulation result may be used as a quantitative evaluation result by the management resource management unit 14.
In addition, about the management simulator 153, since various things are provided as a product version, this can also be utilized. For example, the package software “MAP management simulation II” sold by MP Management Co., Ltd. can be used as the management simulator 153.

  The relevance data management unit 16 generates relevance data indicating the relevance of the management resource to the target business in cooperation with the management resource management unit 15. The relevance data is data having a structure including a plurality of quantitative data groups quantified from a plurality of viewpoints. The relevance data management unit 16 is based on various information accumulated in the business strategy DB 11 and analysis / evaluation result information by the management resource management unit 15 and / or relevance evaluation stored in the rule file 115. Relevance data is generated according to the rules.

Here, the relevance evaluation rule will be described in detail. There are many uncertainties in the degree of association between the target business and management resources. For example, when the management resource is a patent related to pharmaceuticals, usually one patent can cover one product, so that patent is legally effective, marketable, and has business and competitive advantages. The degree of involvement with the patent business can be almost 100%. On the other hand, for example, in a multi-part type product such as an electronic device or a service related thereto, a huge number of patents are related to one product or service. In this case, in addition to the ease of commercialization, the number of patents of other companies, the presence or absence of relative superiority to the patents of other companies, the presence or absence of technical advantages, etc. have a great influence on the performance of the business. For this reason, the degree of relevance of each patent business may be limited to about 0 to several percent. The same applies to relative monopoly rights such as copyrights, rights to use marks for goods / services such as trademark rights, and exclusive monopoly rights relating to the form of goods such as design rights. When management resources are human resources, the specialized fields, skills, and personality of the human resources have a significant impact on the business. When management resources are goods, their performance and quality affect the business. When management resources are funds, they are usually less relevant to the business on its own, and the relationship with the business is strengthened through cooperation with human resources, things, information, and intellectual property tools with skills and motivation. There is such a special situation between business and management resources, but it is usually the source of demand that knows the best degree of relevance of business resources that can be candidates for supply or supply to the business. Or there is an empirical rule of being a supplier (user).
Therefore, in the present embodiment, an action to a user who can be a demand source or a supply source is urged, and a procedure for generating relevance data based on the data obtained thereby is determined for each type of management resource, for each field or product. Things were defined as relevance evaluation rules.

  Specifically, a plurality of input screens for causing the user to perform actions such as data input are prepared in the option DB 114, and the order of reading from the option DB 114 when displaying these input screens on the display, The weighting coefficient for the data input or generated through the display of the hierarchical structure and each input screen is changed for each type of management resource, for each field or product. The set of input quantitative data is arranged in at least a data structure recognized by the server device 2 so that relevance data can be generated.

  For example, as shown in FIG. 8 (a), the relevance data includes, for each management resource used in the target business, the type of “demand / supply”, “type of resource”, and the range in which the management resource is used. “Relevant range” for narrowing down and “feature data” obtained by quantifying the characteristics of the management resources based on a plurality of types of evaluation rules having different viewpoints are arranged in a predetermined order.

  The type of “demand / supply” is a kind of supply-demand ID that represents the supply-demand difference output by the management simulator 153 described above when the user inputs necessary parameters. As the “resource type”, any or some of the data of the plurality of items illustrated in FIG. 8B is set by the user. The data of these items is data quantified by the symbols shown in the right column of FIG. The “related range” is data having a structure illustrated in FIG. That is, the “field” related to the management resource selected by the user, “serendipity”, and “condition” data are constituent elements. In the “field”, when the selected management resource is technology or patent, the data in the classification column of FIG. 4A is set. “Serendipity” is set with an association word (serendipity information) automatically extracted from the association support DB 113 using a word belonging to the classification as a keyword when the data in the classification column is set. The associative word is set to obtain an unexpected result that the user does not notice. The setting of the serendipity information can be turned off. “Condition” is a range of numerical values that the user desires to be matched in the server device 2, for example, in light of the reality that supply and demand rarely match completely, a certain range is determined, and fit within that range I want information. Whether or not to set this “condition” is also arbitrary. When the condition is not set, the fitness is determined based on the condition determined by the server device 2.

  The characteristic data is a set of data of items illustrated in FIG. 8D, that is, a quantitative data group by itself. “A1” to “E1” illustrated in FIG. 8D are data obtained by quantifying the evaluation results for the respective items by numerical values, and “Σ” is a total value thereof. The items “A1” to “E1” include, for example, when the management resource is a patent, the contribution of one patent to the business or product (A1), the ease of commercialization (B1), the marketability (C1), The items “A1” to “A” are items having different viewpoints such as the relative superiority (D1) and the claim period (E1), and the total value (Σ) is in the range of, for example, 0 to 100 points. “E1” is weighted. When all of “A1” to “E1” are equally weighted, the evaluation result of 20 points MAX may be set for each item. The numerical value or weight is automatically calculated and output by the management simulator 153 of the management resource management unit 15 when the user inputs necessary parameters.

The item contents and the number of items “A1” to “E1” are examples, and can be increased or decreased as necessary. Further, an average value may be provided instead of “Σ” which is the total value. For example, FIG. 9A represents the evaluation results of all items “A1” to “E1” and the total value thereof as a distribution of feature data. FIG. 9B and FIG. As shown in c), only one of the items may be selected, and the average value of the evaluation results for the selected item may be used instead of the total value. However, it is desirable to follow common rules for the number of items and how items are handled in the entire network system.
In this way, the degree of relationship between management resources that are the targets of supply and demand with respect to the target business is expressed by relevance data including a quantitative data group. It is expected to be finely tuned and the precision of the supply / demand balance will be precise. In addition, since the relevance data is generated including the serendipity information, there is a possibility that a result unexpected by the user is obtained. 9A and 9C can be realized by drawing processing by the output control unit 14.

  A plurality of relevance data may be generated in one business. In addition, not only “demand” of management resources but also “supply” of management resources may exist simultaneously. For example, in-house, there may be a combination of demand for patents, supply of patents, demand for engineers, and demand for alliance partners (corporate alliances).

  The common data management unit 17 generates common data in which characteristic information representing the characteristics of management resources is expressed in a data format that can be commonly recognized in the network system, and this is generated, for example, in a predetermined area (common data recording area of the management strategy DB 11). ). The common data has a structure shown in FIG. 10, for example. That is, the common data includes the header and a plurality of attached areas (attached # 1 and # 2 in the example of FIG. 10). In the header, information indicating which relevance data corresponds to the header is set. Attached # 1 is attached with a data file in which feature information representing the feature of the management resource input by the user is described in a data format that can be recognized by other terminal devices 1 and server device 2, such as text data. In the attachment # 2, serendipity information extracted from the association support DB 113 using the words included in the feature information as keywords is input. Thereby, the unexpected information more than the user intends can be presented to other users. Note that the data structure shown in FIG. 10 is not necessarily required.

The characteristic information that is the basis of the common data is obtained, for example, by displaying a screen in a predetermined common data input format on the display and thereby arranging the data input by the user in a predetermined order. For example, if the management resource is a patent, the feature information includes the technical field to which the resource belongs, business application data that indicates what kind of business it relates to, data that directly expresses the scope of the patent, For example, review information on the IP tool provided by the organization that holds the patent. The business application data is, for example, data such as the types of businesses that can be implemented, the market size, the types of products that can be introduced into each market, and the contribution rate of the intellectual property tool for these products.
In the case of other management resources, common data is generated and stored in the same procedure as described above.
When the communication with the server device 2 is established, the common data management unit 17 reads the common data corresponding to the management resource that is a candidate for supply or demand using the indirect ID as a key and transmits the data to the server device 2. I will let you.

  When the relevance data and the common data are prepared, the main control unit 10 enables the relevance data and the common data to be transmitted to the server device 2 through the communication control unit 12 together with the user's indirect ID. The relevance data is the relevance data of the demand source for management resources with demand, and the relevance data of the supply source for management resources with supply.

[Server device]
Next, the server device 2 will be described. The server apparatus 2 is an information processing apparatus including an external storage device that includes a server program and a server function-equipped computer as main components. The server program is distributed by being recorded in a computer-readable form on a portable recording medium such as a disk, or distributed in a form that can be downloaded from a program server or the like through the wide area network WN. In the present embodiment, the supply / demand DB 21 is constructed in the external storage device by the server program, and the main control unit 20, the access control unit 22, the supply / demand management unit 23, and the strategy support information management unit 24 are installed in the computer equipped with the server function. Form the function.

  The supply and demand DB 21 is a set of DBs for accumulating information related to the supply and demand of management resources. Specifically, the demand source DB 211 that stores the demand source relevance data transmitted from the terminal device 1 in association with the indirect ID of the demand source, and the relevance data of the supply source transmitted from the terminal device 1 As an optional service for the supply source DB 212 to be stored in association with the indirect ID of the supply source, the introduction DB 213 for storing introduction information about the target management resource, the association support DB 214, and the management resource to be utilized An option DB 215 for storing various information to be provided and a rule book 216 are included. Information accumulated in the demand source DB 211 and the supply source DB 212 is classified for each type of management resource.

  The associative support DB 214 has the same structure as the associative support DB 113 provided in the terminal device 1, but uses information slightly differently. The associative support DB 113 of the terminal device 1 is used for deriving serendipity information that becomes a part of common data or relevance data, while the associative support DB 214 of the server device 2 is used for determining the degree of fitness of supply and demand. Deriving information.

  The information related to the option service stored in the option DB 215 includes, for example, information related to a professional human resource introduction service related to a business resource transaction contract, a service providing detailed business information, and a contract mediation service. These are provided as one of the items on the interface screen of the display of the terminal device 1 that has accessed, and when selected by the user, an optional service corresponding to the item is activated and executed. Yes. The rule book 216 stores various rules including a supply / demand compatibility determination rule and a serendipity conversion rule.

  The introduction information stored in the introduction information DB 213 is, for example, relative data between the management data specified by the relevance data and other management resources held by others, with the common data transmitted from the terminal device 1 together with each relevance data. Evaluation result data, evaluation information indicating objective evaluation contents of a third party for the management resource, external support information for the management resource or the target business, and the like.

  The common data is associated with the relevance data and the indirect ID transmitted therewith. The relative evaluation result data is data (statistical data, patent map data, etc.) representing the relative positioning of the part with respect to the whole. For example, when the management resource is an intellectual property tool, the evaluation information is evaluation information received from the third party operation terminal 5 for any of legal evaluation, technical evaluation, and economic evaluation. This evaluation information is associated with the supplier's general data, and when the general data is read, this evaluation information can be provided together. As a result, an objective judgment material can be given to an organization that purchases or licenses the IP tool. The external support information includes an intellectual property analyst report obtained through the third-party operation terminal 5, recent transaction examples, competitive business capability data, etc., which are also associated with the supplier's common data, When the information is provided to the terminal device 1, it can be provided instead of the evaluation information or together with the evaluation information. Thereby, it is expected that it becomes easy for the user who operates the terminal device 1 to select the target business to utilize the management resources.

  The main control unit 20 performs various controls necessary to operate as the server device 2. Further, if necessary, control of information acquisition from various devices or systems connected to the wide area network WN, instruction to provide information to each terminal device 1, and the like are performed.

  The access control unit 22 enables security communication with all devices or systems connected to the wide area network WN. Security communication can be realized by encryption communication that authenticates whether or not access is accompanied by predetermined authority information and permits communication only with authenticated access. However, of course, it may be realized by other security tools.

  The supply and demand management unit 23 includes a DB manager 231 and a random number generation device 232 as auxiliary tools. The DB manager 231 performs accumulation (file construction) and reading of various information in the supply and demand DB 21. The random number generation device 232 generates a random number for expressing contingency, for example, when determining the degree of fitness of supply and demand. The supply and demand management unit 23 appropriately activates these auxiliary tools, and uses various rules stored in the rule book 216 to determine the suitability of supply and demand in management resources and provide information to the demand source or the supply source. The processing for is performed in cooperation with the main control unit 20.

  FIG. 12 illustrates the concept of supply / demand compatibility determination. The goodness-of-fit determination is a feature of the quantitative data group included in each of the relevance data of all the demand sources accumulated in the demand source DB 211 and the relevance data of all the supply sources accumulated in the supply source DB 212. The comparison is performed for each set of the demand source (demand) and the supply source (supply) specified by the data (demand / supply ID) indicating the type of supply / demand. For the fitness determination, a fitness determination rule R501 and a serendipity conversion rule R502 are used. If necessary, a random number generated by the random number generation device 232 is used as a parameter for matching degree determination, for example, a numerical value representing a range to be determined to be matching.

  The goodness-of-fit determination rule R501 is a rule that defines which range has goodness of fit. For example, the types of management resources (FIG. 8B) are the same, the “fields” in the related range (see FIG. 8C) are the same, and between the features represented by the quantitative data group (FIG. 8D) The difference may be a simple content rule that “conformance is present” if it conforms to the conditions defined in advance in the system, but the related range (the user-specified range included in FIG. Determining whether the conditions according to the “condition” are met meets the needs of the user who is looking for what he wants, for example, the user's scope includes not only “field” but also “serendipity”. The conditions are such that the conformity between “Σ” of feature data is 20% or more, the conformity between “A1” is within 20%, the conformity of “b1” is within 30%, etc. If specified, those that meet the conditions are marked as having `` goodness of fit '' It is preferable to that rule.

  The serendipity conversion rule R502 includes, for example, the serendipity information in the fitness determination parameter (variable that determines the type of information to be used) on the server device 2 when the user does not specify “serendipity” in the related range. Rules are established. For example, information derived from or associated with the keyword is extracted from the association support DB 214 using a word included in the data of the “field” as a keyword, and this information is added to the “serendipity” to determine the fitness. .

  FIG. 13 shows a specific example of supply / demand compatibility determination using the above-described compatibility determination rule R501 and the like. In the example of FIG. 13, in the demand source DB 211, “J” that is a supply and demand ID is set in the head field, and then data “ALm”, “IPn”, “IPm”, “IPq”..., Field data “H03”, “C12”..., Numerical values “20”, “70”, and “85” representing the total value of a plurality of item data are set as feature data A plurality of relevance data is stored in association with “szk0101”, “abc0204”, and “def0311” which are indirect IDs of the demand source. On the other hand, in the supply source DB 212, “K” that is a supply ID is set in the head field, and then data “IPa”, “IPb”, “IPc”,... A plurality of relevance data set with numerical values “40”, “80”, and “90” representing the total value of a plurality of item data as feature data is represented as indirect ID of the supplier Are stored in association with “ghi0355”, “jkl0380”, and “mno0360”. The data representing the type of resource is illustrated in FIG. 7B, and the data representing the field is illustrated in FIG. 7A. In the illustrated example, “conditions” and “serendipity” are not added, and those set by the server device 2 are used. In the server apparatus 2, assuming that the relevance level determination rule for determining that the relevance data in which the “field” is the same and the “feature data” is in the range of 10 to 30% is “applicable”, the server apparatus 2 , The relevance data “J · IPn · H03 · 85... Szk0101” in the demand source DB 211 is the two relevance data “K · IPa · H03 · 90... Ghi0355” and “K · IPb” in the supply source DB 212. · H03 · 80... Jkl0380 ” Then, the common data of the two supply sources can be provided to the terminal device 1 of the demand source. At this time, when evaluation information, external support information, and the like for these resources are recorded in association with each other, they can be provided together. On the other hand, the two supply source terminal devices 1 can be provided with common data of the same demand source. At this time, the existence of the terminal devices 1 as the other supply sources is concealed in the terminal devices 1 as the two supply sources. This can be realized, for example, by identifying the supply / demand ID existing in the first field of the relevance data, and filtering the relevance data so that it can be recognized only from one of the demand source and the supply source. . It is as if “magic mirror” is there.

  The strategy support information management unit 24 performs processing related to management resource push / pull creation support in each organization or individual. Specifically, the information stored in the introduction information DB 213 and the option DB 215 is displayed on the display of each terminal device 1 that has accessed, and the introduction information desired by the user of each terminal device 1 is provided. We provide professional human resource introduction services for business contracts, detailed business information services, contract brokerage services, etc.

[Operation example]
Next, an operation example of the network system configured as described above will be described. As a premise, it is assumed that the terminal device 1 has finished user authentication by the access control unit 13 and the server device 2 has also finished authentication with each terminal device 1.

(1-1) Concept Creation Support Each terminal device 1 has a function of performing concept creation support. The user can select this function when determining the supply and demand of management resources. When the concept creation support function is selected, the management resource management unit 15 of the terminal device 1 activates the search / analysis engine 151 to obtain concept level information from a wide variety of information stored in the management strategy DB 11. Perform processing for sorting. In other words, the process of making the user's ambiguous idea into a form is performed. This process is started when the user inputs a plurality of words or phrases at random. When receiving the input of a large number of words or phrases from the user, the search / analysis engine 151 searches the management strategy DB 11 and extracts a large number of short phrases included in the already accumulated information. At this time, keywords related to the input word or phrase are extracted from the association support DB 113, and a short phrase including these keywords is generated and output. For example, if the input word or phrase is “new business, development of new fields, for children, niche, health, minimum investment, limited to the region”, the search / analysis engine 151 will display “Marshmallows to cultivate biting power”, “ The phrases “pedometer”, “soccer with OO”, “small pendant type aroma dispenser ...”, etc. are output continuously. These phrases are sequentially displayed on the display of the terminal device 1. The user sees these phrases and inflates the concept. As you enter new words or phrases to narrow down the relevant market information in detail, the aroma dispenser can also be used for character design for children. It's possible and it's safe. The aroma dispenser, which has recently been reported to be effective in suppressing the new flu, can be incorporated into this aroma dispenser to make it easier for the niche positioning leader to be seated. Inflates.

(1-2) Generation of relevance data and common data As a result of the concept creation support described above, the user sets the manufacture and sale of an aroma dispenser as a target business, management resources necessary for the target business, and future business The management simulator 152 is made to predict the development. According to this prediction, business development is good, but technology related to microwave oscillation and related patents will be indispensable for making aroma dispensers. At the same time, it can be seen that micro-oscillation technology is a technology that our company does not have, and furthermore, it does not have sufficient patents and human resources are not necessarily sufficient. Therefore, the user causes the terminal device 1 to generate relevance data and common data indicating that there is a demand for management resources for the target business. The relevance data is identification data representing demand, the type of resource in demand, the data of a related range including the field of aroma dispenser, serendipity information and conditions, and characteristic data. The conditions are: among the feature data, for patents, a quantitative data group representing numerical values derived by the management simulator 152, a weighting factor that emphasizes legal stability of patents in demand, and “Σ” is 50%. It is assumed that the data fits within the range. The common data is generated based on characteristic information such as “aroma dispenser, aroma, cloud fog, microwave oscillation, influenza suppression...”.
The terminal device 1 transmits such relevance data and common data to the server device 2 together with its own indirect ID.

(1-3) Supply / Demand Compatibility Degree Determination The server device 2 (supply / demand management unit 23) uses the above condition data among the relevance data from each terminal device 1 stored in the demand source DB 211 and the supply source DB 212. A pair of supply and demand in a suitable range is specified, for example, in the manner illustrated in FIG. And the common data and indirect ID of the supplier which match condition data are distributed to the user's terminal device 1 which concerns on a demand source. When evaluation information or external support information is linked to the common data, such information is also distributed.

(1-4) Business Resource Transaction Judgment Support The user refers to the common data and other information distributed to the terminal device 1 to determine whether the management resource of the supplier is attractive for the company. When it is determined that the management resource is useful for the company, the server apparatus 2 is requested to perform a direct negotiation or a negotiation with an expert. At the time of direct negotiation, the server device 2 notifies the supplier that sent the indirect ID to that effect and supports the exchange of personal information between the parties. When a negotiation request is made by an expert, an expert is dispatched. Note that the user A can also make a negotiation consultant support request from the terminal device 1 to the server device 2.
In this way, negotiations according to the company's strengths become possible.

[Modification of First Embodiment]
In the first embodiment, it is possible to provide the terminal device 1 related to the demand source from the server device 2 to the common data, evaluation information, and indirect ID (supply source information) of the supply source, and to the terminal device 1 related to the supply source. Has shown an example in which common data of demand sources and indirect IDs (demand source information) can be provided. However, a form in which relevance data of matching partners can also be provided is possible. In other words, the server device 2 can provide the terminal device 1 related to the demand source by including the relevance data of the supply source in addition to the common data of the supply source in the supply source information. The demand source information may include the relevance data of the demand source in addition to the common data of the demand source. By receiving such relevance data of the matching partner, the terminal device 1 can analyze the detailed relevance between the received relevance data and the company's relevance data in more detail.

  As described above, according to the network system of the present embodiment, the server device 2 provides the user terminal device 1 with the supply information of the management resource that is highly likely to meet the demand. Information on where and how much of the management resources are located can be easily obtained, and pull creation support for users can be realized. On the other hand, the terminal device 1 of the user who wants to supply management resources is provided with the demand source information of the management resources that are likely to be suitable for the supply, so where and where the demand for the management resources that can be supplied by each company It is possible to obtain information about whether or not there is a place, and support for creating a push for the user is realized. This makes it possible to find the right person in the right place by matching business strategy and management resources. Without this network system, even if the thresholds are high, access through the system is possible.

Second Embodiment
Next, a second embodiment of the present invention will be described. In this embodiment, the server device 2 described in the first embodiment, in particular, the search function using the association support DB 214 is enhanced. Even if the information on the resource to be utilized is distributed from the server device 2 to the user's terminal device 1, the user generally performs further information retrieval in order to verify the certainty of the information on the resource. Is. In this case, in the well-known search engine such as Google, which is provided by Google Inc. in the United States, the page linked from many pages is judged as a “page with useful information”, and the rank is raised. In addition, pages that are linked from high-ranking pages are ranked so as to obtain a high evaluation, so that “highly referenced popular pages” are displayed at the top. Recently, a service for providing similar keywords for a certain search keyword has also been provided. However, the information obtained by such a search engine is, in the end, homogeneous. This is because the page to be linked and the page to be pasted have the same content. With conventional search methods, it is difficult to say that the connection of a small group of information or knowledge that is divided and scattered like the island universe is not sufficient. The DB and search engine with the chance and unexpectedness to meet different information expands the range of concept creation described above, and finds the relevance between scattered information and knowledge to create new knowledge. I think that. In order to achieve the purpose of creating new business and new products based on the creation of a novel concept, there is a limit to the conventional search methods represented by Google. The search method described in this embodiment is one method that breaks this limit.

  The server device 2 of this embodiment receives, for example, information related to supply and demand of management resources, and gives a user who desires further information retrieval based on the information, chance of chance and chance of unexpectedness / association with different information. is there. In this embodiment, the term “keyword” is used. However, when it is necessary to particularly distinguish these, the keyword that the user regularly uses is the regular keyword, and the keyword that is the processing target among the regular keywords is the title keyword, Of the common keywords, a keyword that can be associated with the title keyword is referred to as an associative keyword, a keyword that is actually used for the search is referred to as a search keyword, and a keyword that the user inquires of the server device 2 is referred to as a search keyword candidate.

The server device 2 of this embodiment is assumed to further include the function and DB illustrated in FIG. 14 in addition to the configuration of the first embodiment shown in FIG.
That is, an I / O control unit 31 that performs input / output control with an external device, a keyword management unit 32 that manages recording / reading of various keywords described above, a table management unit 33 that generates or updates a relationship table, The functions of a request reception unit 34 that receives a request from a user, a search unit 35 that is a new search engine, and an evaluation unit 36 that evaluates a search result are formed, and a keyword DB 37 is constructed in the storage device.
The external device connected to the I / O control unit 31 is, for example, an acquisition source of source document data for extracting a keyword that can be a title keyword or an associative keyword, and an accumulation source of electronic dictionary data that is a source of an ordinary keyword. Or it is the terminal device 1 which performs an information request.

  In the keyword DB 37, a plurality of common keywords, which are electronic dictionary data or data designated by the user, are stored together with IDs for identifying individual common keywords. Common keywords are sorted in alphabetical order. The ID is an index number associated with each sorted common keyword on a one-to-one basis. All keywords handled in this embodiment are uniquely identified by this index number.

  The server device 2 first extracts the title keyword and the associative keyword from the source document data, and derives the relationship between them. FIG. 15 is an explanatory diagram of the operation procedure of the server device 2 at this time. Referring to FIG. 15, the keyword management unit 32 reads the source document data in units of pages or files (in the case of data that does not have the concept of pages, in units of files) (step S201). At this time, although it is not an essential process, appropriateness diagnosis of data in a page or a file is performed (step S202). The appropriateness diagnosis is a process for checking whether or not the data is intentionally conscious of statistical data. For example, when a plurality of the same keywords exist in one sentence, reading from the page or file is stopped as inappropriate data.

  If the data is appropriate as a result of the appropriateness diagnosis, the keyword management unit 32 specifies the title area of the read file by a known area cutout process used in character recognition or the like. The title area is an area of the header portion at the head of the file, and is an area to which headings such as “Introduction” and “Prolog” are attached, although it varies depending on the type of source document data. When such a headline does not exist, a chunk part of about several hundred words from the head may be used as the title area. In general, it is common to write from the conclusion first, from business documents to essays and Web pages. Important keywords tend to appear in the title area. Therefore, in order to specify such an important keyword, a predetermined number of characters are extracted from the title area, and keyword extraction is performed by word division using a conjunction, a blank, a cloud, a symbol, an English word, etc. as a boundary (step S203).

  Next, the number of extracted keywords is accumulated to identify the most frequently appearing keywords. Then, referring to the keyword DB 37, if there is a matching common keyword in the keyword DB 37, the common keyword is determined as the title keyword (step S204). If there is no matching common keyword in the keyword DB 37, a common keyword that matches the keyword with the next highest appearance frequency is searched for, and if found, it is determined as the title keyword.

Thereafter, word decomposition is performed again from the beginning to the end of the page or file, and keywords other than the title keyword are extracted, and it is confirmed whether the same keyword as the extracted keyword exists in the keyword DB 37. If it exists, each keyword is defined as an associative keyword, and an index number is assigned thereto. Then, the appearance frequency for each associative keyword is scored. In this embodiment, the scoring result is obtained by associating the individual keyword with the title keyword (step S205). The association degree is a numerical value in percent display obtained by dividing the number of appearances of each association keyword by the total number of keywords existing in the page or file in which the title keyword exists and multiplying by 100. A point converted according to a predetermined rule can also be used as the association degree. The word decomposition here is performed at a level as fine as possible so that the degree of association with the title keyword can be checked in detail. For example, when the phrase “book of intellectual property” exists in the page, it is preferably broken down into four words of “intellectual”, “property”, “no”, and “book”. The association degree (appearance frequency) of the keyword “book” in this sentence is 1 ÷ 4 × 100 = 25%. Thereafter, an appropriate association degree range is determined according to the following rules.
Undervalue <appropriate association (1-10%) <overvalue Overvalue means that it appears excessively on the entire page or file. This is excluded because it results in biasing the degree of association. Undervalue is rarely used and is therefore removed for similar reasons.

In this manner, when the association degree of a plurality of association keywords in the page or file in which the title keyword exists is derived, the keyword management unit 32 causes the table management unit 33 to manage the relevance table. The table management unit 33 extracts the title keyword and its index number from the keyword DB 37, and associates the index number of each associative keyword and the association degree (%) derived for each associative keyword with the title keyword, A relevance table representing the relevance between the title keyword and each associative keyword is generated (step S206).
The above processing is repeated for other pages or files (step S207: Yes). Thereby, a relevance table is generated for each title keyword and stored in the association support DB 214.

Next, an information search procedure using the relevance table will be described. FIG. 16 is an explanatory diagram of the operation procedure of the server device 2 at this time.
A user operates the terminal device 1 to transmit a search request with search keyword candidates to the server device 2 in order to search for information related to resource utilization support. When the server 2 receives the request at the request receiving unit 34 (step S301), the search unit 35 searches the association support DB 214 for a title keyword relevance table that matches the search keyword candidate (step S301). Step S302). If the relevance table does not exist, the subsequent search processing is stopped (step S303; No). If it exists, an associative keyword corresponding to each index number is specified from the keyword area of the keyword DB 37 based on some index numbers recorded in the relevancy table (steps S303; Yes, S304). Then, a list in which these are listed is generated, a list ID is assigned to the list, and the list ID and the index number of the associated keyword are recorded in a temporary file (not shown). The associative keywords listed are potential search keywords that can be employed as search keywords. When the recording to the temporary file is completed, the search unit 35 provides a list of each associative keyword together with the list ID to the terminal device 1 that issued the search request (step S305).

When any associated keyword is adopted as a search keyword in the terminal device 1 that has received the list, the list ID and the index number of the associated keyword adopted in the list are returned to the server device 2. Accordingly, the evaluation unit 36 refers to the temporary file to detect which associative keyword is adopted as the search keyword in the terminal device 1 and transmits the result to the table management unit 33. The table management unit 33 calculates the number of detections by the evaluation unit 36, and cumulatively records the calculation result in the association table in association with the index number of the associated keyword (step S306; Yes, S307). This number of times of detection becomes information indicating the usage of the associative keyword. The table management unit 33 sorts the recorded contents of the relevance table each time the contents are updated. In the relevance table, the index number of the associative keyword having the higher association degree with respect to the title keyword of the first field is rearranged in the earlier field. The usage is recorded as accompanying information.
If it is detected that another associated keyword in the list is adopted, the processes after step S306 are repeated (step S308; No).

  An example of the relationship table updated in this way is shown in FIG. In the example of FIG. 17, “Intellectual Property” is defined as the title keyword. This “intellectual property” and the index number (ID of “intellectual property”; “1287366”) in the keyword DB 37 are stored in the first field, and the index number “121245” of “patent” and its association are in descending order of association. Degree “20.13”, utilization degree “0012”, “legal” index number “1183324” and association degree “10.31”, utilization degree “0052”, index number “52447122” and “association” The degree “08.66” and the utilization degree “0102”... Are stored.

By the way, identification of some associative keywords in the process of step S304 and creation of a list in the process of step S305 are performed as follows, for example.
That is, from the recorded information in the association table illustrated in FIG. 17, IDs of some associative keywords having a relatively high association degree (appearance frequency), IDs of some associative keywords having a relatively low association degree, and use ID of some associative keywords with a relatively high degree (accumulated value of the number of detections), ID of some associative keywords with a relatively low degree of usage, associating degree or usage, and a search request source At least one of the IDs of the associative keywords within the range designated by the terminal device 1 is specified, and a list of associative keywords corresponding to the specified ID is generated. The list of generated associative keywords is, for example, as shown in FIG. In the figure, “List-ID102355” shown in the upper right is the list ID.

In FIG. 18A, “Top 5” has the top five associative keywords having the highest degree of association with the title keyword “Intellectual Property”, and “Bottom 5” has the association degree with the title keyword “Intellectual Property”. Five associative keywords counted from the lowest, “Random 5” are five associative keywords whose degree of association or usage is specified by a random number generated by the random number generation device 232, and “User setting 5” is a search request Are the five associative keywords specified by the conditions set by the user at the time (for example, the usage is high, the field is the same, and the association is high). FIG. 18B shows that the user has adopted “fiber” and “medicine” as search keywords from such a list. By transmitting the IDs of “fiber” and “medicine” together with the list ID to the server device 2, the server device 2 side cumulatively records the usage (times) in the relevance table. .
By sending such a list to the sender of the search request, the user of the sender can be given an opportunity to touch different information that he / she did not notice. As a result, compared to conventional search methods that can only obtain the same quality of information, it is possible to search for information with a wider range, and it is expected to have an excellent effect that the selection range for resource utilization can be greatly expanded. it can.
In FIGS. 18A and 18B, an example of a keyword consisting of 2 to 3 characters is given for convenience, but the number of characters is arbitrary. Moreover, it is not necessarily limited to five associative keywords.

As mentioned above, although this invention was demonstrated based on several embodiment, the network system of this invention is not only the information processing apparatus which exists independently as the server apparatus 2, but the apparatus which added the server function to the terminal device 1. FIG. Can be implemented.
In the above description, management resources are given as examples of resources to be utilized. However, the present invention can be similarly applied to resources used for public purposes not necessarily directly related to management.

1 is an overall configuration diagram of a network system according to an embodiment of the present invention. The functional block block diagram of the terminal device of this embodiment. The figure which showed the example of an interface screen when searching the resource information classified focusing on the intellectual property tool. (A) is a screen example of the organization / classification result of the company patent, (b) is a screen example of a decision tree which is one of decision making tools, and (c) is a screen example showing the contents of human resources. . (A) is a screen example of marketing information, (b) is a screen example of financial information, (c) is a diagram showing a screen example of cost. The figure which showed the example of the content of the quantitative evaluation rule. (A), (b) is the figure which showed the example of the content of the corresponding | compatible rule, respectively. (A) is a structural example of relevance data, (b) is a resource type in relevance data, (c) is a relevance range in relevance data, (d) is feature data (quantitative data group) in relevance data. The figure shown. (A) is an example of characteristic data including evaluation results of five items and their total values, (b) is an example of narrowing down to three items, and (c) is an evaluation result of items narrowed down as in (b). The figure which showed the example of the feature data containing the average value. Structure explanatory drawing of common data. The functional block block diagram of the server apparatus by this embodiment. FIG. 3 is a conceptual explanatory diagram of fitness determination in a server device. Explanatory drawing which showed the specific example of the fitness determination. The function block diagram for the additional part of the server apparatus used as 2nd Embodiment of this invention. Explanatory drawing of the operation | movement procedure of a server apparatus when producing | generating the relevance table for every title keyword. Explanatory drawing of the operation | movement procedure of a server apparatus when providing an associative keyword based on a search request. The figure which shows the example of the content of a relevance table. (A) is the figure which showed an example of the list | wrist of an association keyword, (b) is explanatory drawing of the association keyword selected from the list by the user.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Terminal device, 2 ... Server device, 3 ... Public organization system, 4 ... Data bank, 5 ... Third party operation terminal, 6 ... Expert system, 10 ... Main control unit of terminal device, 11 ... management strategy DB, 111 ... internal resource DB, 112 ... external resource DB, 113 ... association support DB, 114 ... option DB, 115 Rule file, 12... Terminal device communication control unit, 13 terminal device input control unit, 14 terminal device output control unit, 15 terminal device management resource management unit, 151 ... DB manager, 152 ... Search / analysis engine, 153 ... Management simulator, 16 ... Relevance data management unit, 17 ... Common data management unit, 20 ... Main control of server device Part, 21 ... Supply-demand DB, 21 ... Demand source DB, 212 ... Supplier DB, 213 ... Introduction information DB, 214 ... Associative support DB, 215 ... Option DB, 216 ... Rule book, 22 ... Server Access control unit of apparatus, 23 ... Strategy support information management unit, 31 ... I / O control unit, 32 ... Keyword management unit, 33 ... Table management unit, 34 ... Request reception unit, 35 ... Search unit, 36 ... Evaluation unit, 37 ... Keyword DB, WN ... Wide area network.

Claims (17)

A method executed by a server device and a plurality of user devices respectively connected via a network,
The first user device operated by a user who can be a demand source of resources to be utilized and the second user device operated by a user who can be a resource supply source have different viewpoints on the characteristics of the resources. By quantifying based on a plurality of types of evaluation rules, the server device is converted into a quantitative data group in a data format that can be recognized by the server device, and feature information for transmitting the resource to other users And convert the quantitative data group and the common data to the server device together with a supply and demand ID for identifying the demand source or the supply source of the resource, respectively. Stages,
The server device stores the quantitative data group and the common data received from the first user device and the second user device in a predetermined storage device in association with the supply and demand ID, respectively, and the stored quantitative data By comparing each feature represented by a group for each set of a demand source and a supply source specified by the supply and demand ID, a matching degree between the demand and supply of the resource is determined, and the first user device has Enabling supply of the supplier's common data having the fitness level within a predetermined range, and enabling the second user device to provide the demand source's common data with the fitness level being within the predetermined range. Resource utilization support method. Each of the first user device and the second user device transmits an indirect ID for indirectly identifying an attribute of a user who operates the first user device to the server device,
When the server device accumulates the indirect ID received from each user device in the storage device in association with the common data from the user device, and provides the common data of the supply source to the first user device Makes it possible to provide the indirect ID of the supply source and conceal the indirect ID of the other demand source. On the other hand, when providing the second user device with the common data of the demand source, the indirect ID of the demand source is provided. Make it possible to conceal the indirect IDs of other suppliers,
The utilization support method according to claim 1. The server device acquires at least one of evaluation information representing a third party evaluation result for the resource of the supplier and support information representing an example of utilization of the resource, and the acquired evaluation information or the support information is acquired. , Storing in the storage device in association with the general data of the supplier, and providing at least one of the evaluation information and the support information when providing the general data,
The utilization support method according to claim 2. The server device associates a keyword DB storing a plurality of keywords related to the use of the resource, and IDs of a plurality of associative keywords associated with the keywords with each occurrence frequency in the source document data for each keyword. Relevance table
When a search request with a search keyword candidate is received from the first user device or the second user device, it is an associative keyword associated with a keyword that matches the search keyword candidate, and its appearance frequency is within a predetermined range. A number of associated keywords belonging to the keyword table are extracted from the keyword DB based on the record information of the relevancy table, and the extracted associated keywords can be provided as potential search keywords to the user device that is the source of the search request.
The utilization support method according to claim 1, 2 or 3.   Each time the server device detects that any of the associative keywords provided to the source user device is adopted as a search keyword, the relevancy table area associated with the ID of the associative keyword The utilization support method of Claim 4 which records the information showing the utilization degree of the said associative keyword. The server device includes, from the recorded information in the association table, some associative keywords having a relatively high appearance frequency, some associative keywords having a relatively low appearance frequency, and the source of the appearance frequencies. Identifying at least one of the associative keywords within the range specified by the user device, and extracting the identified associative keywords,
The utilization support method according to claim 5. An information processing apparatus constituting a network system for supporting resource utilization together with a server apparatus connected via a network,
Quantitative data group in a data format that can be recognized by the server device by the user operating the device quantifying the characteristics of the resource to be supplied or supplied based on a plurality of types of evaluation rules having different viewpoints. First data converting means for converting to
Second data conversion means for converting feature information for allowing other users to recognize the resource into general data in a data format that can be recognized by the server device and other information processing devices;
The quantitative data group and the common data are transmitted to the server device together with a supply and demand ID for identifying a demand source or a supply source of the resource, respectively, and a comparison between features represented by the quantitative data group is performed based on the supply and demand ID. Receive either supply source information including the common data of the supply source or demand source information including the common data of the demand source from the server device performed for each specified demand source and supply source pair. Communication means;
An information processing apparatus comprising: output control means for enabling supply source information or demand source information received by the communication means to be presented to the user through a predetermined output device. For each keyword, an association support DB that accumulates serendipity information that can be associated with the keyword and is selected by a person other than the user or caused by an action of a person other than the user. In addition,
The second data generation means extracts serendipity information corresponding to a keyword included in the feature information from the association support DB, and includes the extracted serendipity information in the feature information and converts it into the common data.
The information processing apparatus according to claim 7. The first data generation means extracts serendipity information corresponding to a keyword included in the resource feature from the association support DB, and converts the extracted serendipity information into the quantitative data group including the resource feature. ,
The information processing apparatus according to claim 8. An information processing apparatus constituting a network system for resource utilization support together with a plurality of user devices,
From each user device, the quantitative data group quantitatively converted into a data format that can be recognized by the own device based on a plurality of types of evaluation rules having different viewpoints of the resources to be supplied or supplied, and Supply / demand for identifying the demand source or the supply source of the resource, respectively, from the common data obtained by converting the characteristic information for causing other user devices to recognize the resource into a data format that can be recognized by the own device and the other user device. Receiving means for receiving together with the ID;
A supply and demand DB that stores the quantitative data group received from each user device and the common data in association with the supply and demand ID;
By comparing the features of the quantitative data group stored in the supply and demand DB for each set of the demand source and the supply source specified by the supply and demand ID, the degree of fitness of the supply and demand is determined, and the user device related to the demand source Makes it possible to provide supplier information including common data of a supplier whose fitness is within a predetermined range, while demand for the user device related to the supplier includes common data of a demand source whose fitness is within a predetermined range. An information processing apparatus comprising: supply and demand management means that can provide original information. The supply and demand management means conceals other demand source information when providing the supply source data when there are a plurality of demand sources of the resource, and on the other hand, when there are a plurality of supply sources of the resource. Is to conceal other supplier information when providing the demand source general data,
The information processing apparatus according to claim 10. A keyword DB storing a plurality of keywords together with an ID for identifying each keyword;
One of the keywords stored in the keyword DB is defined as a title keyword, and the same keywords as those stored in the keyword DB are extracted from the source document data, excluding the title keyword. Keyword management means for determining each keyword as an associative keyword and deriving the appearance frequency of each associative keyword in the source document data;
Extracting the title keyword and the ID of each derived association keyword from the keyword DB, and associating the ID of each association keyword and the appearance frequency derived for each association keyword with the title keyword, Table management means for generating a relevance table representing the relevance between the title keyword and each associative keyword, or updating the recorded information;
Keyword candidate accepting means for accepting input of search keyword candidates for searching for information related to the resource utilization support;
It is checked whether or not there is a relevance table of title keywords that matches the search keyword candidate received by the keyword candidate receiving means, and if it exists, the keyword DB is based on a plurality of IDs recorded in the relevance table. A search means for extracting the associated keyword corresponding to each ID from the search keyword and providing the extracted associated keyword to the sender of the search keyword candidate as a potential search keyword that can be adopted as a search keyword;
The information processing apparatus according to claim 10. The keyword management means measures the appearance frequency of a plurality of extracted keywords extracted from the title area in the source document data in the title area, and the same keywords as these extracted keywords are stored in the keyword DB. And if it is stored, the same keyword as the extracted keyword having the highest appearance frequency is determined as the title keyword.
The information processing apparatus according to claim 12. Having a detecting means for detecting that any of the associative keywords provided to the sender is adopted as a search keyword;
The table management means cumulatively records the number of times of detection by the detection means in the association table in association with the ID of the associative keyword;
The information processing apparatus according to claim 13. The search means, from the record information of the association table, IDs of some associative keywords having a relatively high appearance frequency, IDs of some associative keywords having a relatively low appearance frequency, and the number of detections IDs of some associative keywords with relatively high cumulative values, IDs of some associative keywords with relatively low cumulative values, association frequencies within the range specified by the source of the appearance frequency or the cumulative value Identifying at least one of the keyword IDs, and extracting an associative keyword corresponding to the identified ID from the keyword DB;
The information processing apparatus according to claim 14. A computer program for operating a computer as a user device constituting a network system for resource utilization support together with a server device connected through a network, the computer comprising:
Quantitative data group in a data format that can be recognized by the server device by the user operating the device quantifying the characteristics of the resource to be supplied or supplied based on a plurality of types of evaluation rules with different viewpoints. First data converting means for converting to
Second data conversion means for converting feature information for allowing other users to recognize the resource into general data in a data format that can be recognized by the server device and other information processing devices;
The quantitative data group and the common data are transmitted to the server device together with a supply and demand ID for identifying a demand source or a supply source of the resource, respectively, and a comparison between features represented by the quantitative data group is performed based on the supply and demand ID. Receive either supply source information including the common data of the supply source or demand source information including the common data of the demand source from the server device performed for each specified demand source and supply source pair. Communication means, and
A computer program for resource utilization that causes supply source information or demand source information received by the communication means to function as output control means that can be presented to the user through a predetermined output device. A computer program for operating a computer having a storage device as a server device constituting a network system for supporting resource utilization together with a plurality of user devices connectable through a network, and constructing a supply and demand DB in the storage device And the computer
From each user device, a quantitative data group in which the characteristics of the resource to be supplied or supplied are quantitatively converted into a data format that can be recognized by the device based on a plurality of types of evaluation rules with different viewpoints, and For identifying the demand source or the supply source of the resource, respectively, by converting the common data obtained by converting the feature information for causing the other user device to recognize the resource into a data format that can be recognized by the own device and the other user device. Receiving means for receiving together with the supply and demand ID;
DB management means for storing the quantitative data group and the common data received from each user device in the supply-demand DB in association with the supply-demand ID;
By comparing the features of the quantitative data group stored in the supply and demand DB for each set of the demand source and the supply source specified by the supply and demand ID, the degree of fitness of the supply and demand is determined, and the user device related to the demand source Makes it possible to provide supplier information including common data of a supplier whose fitness is within a predetermined range, while demand for the user device related to the supplier includes common data of a demand source whose fitness is within a predetermined range. Function as a supply and demand management means that can provide original information,
Computer program for resource utilization support.

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