JP7533617B2 - Case example output device, case example output method, and program - Google Patents

Description

The present invention relates to technology for business matching between companies.

A business matching system is used that presents combinations of companies suitable for transactions. The business matching system described in Patent Document 1 extracts effective business partners for the companies to be matched based on segment data that classifies company attribute data, financial data, and transaction data according to specified classification items.

JP 2017-182243 A

Although the business matching system described in Patent Document 1 extracts business partners of companies that are candidates for matching based on segment data, there is room for improvement in terms of presenting highly useful matching examples.

One aspect of the present invention has been made in consideration of the above problems, and one example of its objective is to provide technology that enables the output of highly useful matching examples in business matching between companies.

A case example output device according to one aspect of the present invention comprises a first extraction means for referencing a storage device in which collaboration desire information of each of a plurality of companies is stored, and extracting from the plurality of companies a first company having a collaboration desire similar to the collaboration desire of a target company based on the collaboration desire information of the target company, a second extraction means for extracting from the plurality of companies a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company, and an output means for outputting a matching example relating to the content of collaboration between the first company and the second company.

In one aspect of the present invention, a case example output method includes a case example output device that references a storage device in which collaboration desire information of each of a plurality of companies is stored, extracts from the plurality of companies a first company having a collaboration desire similar to the collaboration desire of a target company based on the collaboration desire information of the target company, extracts from the plurality of companies a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company, and outputs a matching case example regarding the content of collaboration between the first company and the second company.

A program according to one aspect of the present invention is a program that causes a computer to function as a case example output device, the program causing the computer to function as: a first extraction means that references a storage device in which collaboration desire information of each of a plurality of companies is stored, and extracts from the plurality of companies a first company that has a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company; a second extraction means that extracts from the plurality of companies a second company that has a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company; and an output means that outputs a matching example regarding the content of collaboration between the first company and the second company.

According to one aspect of the present invention, it is possible to output matching examples that are highly useful in business matching between companies.

1 is a block diagram showing a configuration of a case example output device according to a first exemplary embodiment of the present invention; 1 is a flow diagram showing the flow of a case output method according to an exemplary embodiment 1 of the present invention. FIG. 11 is a block diagram showing a configuration of a case example output system according to an exemplary embodiment 2 of the present invention. FIG. 11 is a flow chart showing the flow of a case output method according to an exemplary embodiment 2 of the present invention. FIG. 11 is a block diagram showing a configuration of a case example output system according to an exemplary embodiment 3 of the present invention. FIG. 11 is a diagram showing a specific example of a needs information database according to the third exemplary embodiment of the present invention. FIG. 11 is a diagram showing a specific example of a case database according to an exemplary embodiment 3 of the present invention. FIG. 11 is a flow chart showing the flow of a case output method according to an exemplary embodiment 3 of the present invention. FIG. 11 is a diagram showing an example of a screen displayed in exemplary embodiment 3 of the present invention. FIG. 11 is a block diagram showing a configuration of a case example output system according to an exemplary embodiment 4 of the present invention. FIG. 13 is a diagram showing a specific example of a company information database in exemplary embodiment 4 of the present invention. FIG. 11 is a flow chart showing the flow of a case output method according to an exemplary embodiment 4 of the present invention. FIG. 13 is a block diagram showing a configuration of a case example output system according to an exemplary embodiment 5 of the present invention. FIG. 11 is a flow chart showing the flow of a case output method according to an exemplary embodiment 5 of the present invention. FIG. 13 is a diagram showing an example of a screen displayed in exemplary embodiment 5 of the present invention. FIG. 13 is a diagram showing an example of a screen displayed in exemplary embodiment 5 of the present invention. FIG. 13 is a diagram showing an example of a screen displayed in exemplary embodiment 5 of the present invention. FIG. 2 is a block diagram showing an example of a hardware configuration of a case example output device in each exemplary embodiment of the present invention.

[Example embodiment 1]
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A first exemplary embodiment of the present invention will be described in detail with reference to the accompanying drawings. This exemplary embodiment is a basic form of the exemplary embodiments described below.

<Configuration of the case example output device>
The configuration of a case example output device 100 according to this exemplary embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the configuration of the case example output device 100. The case example output device 100 is a device that outputs matching cases relating to the contents of collaboration between companies.

As shown in FIG. 1, the case example output device 100 includes a first extraction unit 101, a second extraction unit 102, and an output unit 103. The first extraction unit 101 is configured to realize a first extraction means in this exemplary embodiment. The second extraction unit 102 is configured to realize a second extraction means in this exemplary embodiment. The output unit 103 is configured to realize an output means in this exemplary embodiment.

The first extraction unit 101 refers to a storage device in which the collaboration desire information of each of a plurality of companies is stored, and extracts from the plurality of companies a first company that has a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company. The collaboration desire information is information indicating the content of the collaboration desire (needs) of the companies. The collaboration desire information includes, for example, information indicating the company name, the content of the business to be collaborated on, the company philosophy, and the services/products that the company can provide. The number of first companies extracted by the first extraction unit 101 may be one or more.

Here, the storage device may be included in the case output device 100, or may be an external device communicatively connected to the case output device 100. For example, the first extraction unit 101 performs natural language processing such as morphological analysis on the collaboration desire information of each of the multiple companies to analyze it, and extracts a first company having a collaboration desire similar to the collaboration desire of the target company based on the analysis result. A known technology can be adopted as a technology for determining the similarity between the collaboration desire information. However, the process of extracting a first company similar to the target company by referring to the collaboration desire information of each company is not limited to the above-mentioned process.

The second extraction unit 102 extracts, from among the multiple companies, a second company having a collaboration desire similar to the collaboration desire of the first company, based on the collaboration desire information of the first company. The number of second companies extracted by the second extraction unit 102 may be one or more. For example, the second extraction unit 102 performs natural language processing such as morphological analysis on the collaboration desire information of each of the multiple companies to analyze it, and based on the analysis result, extracts a second company whose collaboration desire information is similar to that of the first company identified based on the target company. A publicly known technology can be adopted as a technology for determining the similarity between the collaboration desire information. However, the process of extracting a second company by referring to the collaboration desire information of each company is not limited to the above-mentioned process.

The output unit 103 outputs a matching case relating to the content of collaboration between a first company and a second company. For example, the output unit 103 outputs information indicating the matching case to a display device. Hereinafter, the information indicating the matching case is also described as matching case information. Hereinafter, the display device may be included in the case output device 100, or may be an external device communicatively connected to the case output device 100. The output unit 103 may also output the matching case information to another device such as a speaker or an image forming device, or may output the matching case information to an external storage device for storage. However, the process of outputting the matching case is not limited to the process described above.

<Flow of example output method>
The flow of the case example output method S100 executed by the case example output device 100 configured as above will be described with reference to Fig. 2. Fig. 2 is a flow diagram showing the flow of the case example output method S100. As shown in Fig. 2, the case example output method S100 includes steps S1 to S3.

(Step S1)
In step S1, the first extraction unit 101 refers to a storage device in which the collaboration desire information of each of the multiple companies is stored, and extracts from the multiple companies a first company that has a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company.

(Step S2)
In step S2, the second extraction unit 102 extracts, from among the multiple companies, a second company having a collaboration desire similar to the collaboration desire of the first company, based on the collaboration desire information of the first company.

(Step S3)
In step S3, the output unit 103 outputs a matching example regarding the contents of collaboration between the first company and the second company.
<Advantages of this exemplary embodiment>
As described above, the case example output device 100 according to the present exemplary embodiment outputs not only the matching case of the target company, but also the matching case information indicating the matching case of the first company having a collaboration desire similar to the collaboration desire of the target company. As a result, the case example output device 100 according to the present exemplary embodiment can output highly useful matching case information that can be used as a reference for business matching of the target company.

Exemplary embodiment 2
A second exemplary embodiment of the present invention will be described in detail with reference to the drawings. Note that components having the same functions as those described in the first exemplary embodiment are denoted by the same reference numerals, and the description thereof will not be repeated.

<Configuration of the case example output system>
The case example output system 1 according to the second exemplary embodiment is a system that presents matching cases relating to collaboration between companies to a user. The configuration of the case example output system 1 will be described with reference to Fig. 3. Fig. 3 is a block diagram showing the configuration of the case example output system 1. As shown in Fig. 3, the case example output system 1 includes a case example output device 10 and a user terminal 3. The case example output device 10 and the user terminal 3 are connected to each other so as to be able to communicate with each other.

(Configuration of the case example output device)
The case example output device 10 includes a first extraction unit 11, a second extraction unit 12, and an output unit 13. The first extraction unit 11 is configured to realize a first extraction means in this exemplary embodiment. The second extraction unit 12 is configured to realize a second extraction means in this exemplary embodiment. The output unit 13 is configured to realize an output means in this exemplary embodiment.

The first extraction unit 11 differs from the first extraction unit 101 in exemplary embodiment 1 in that it receives input information indicating a target company among a plurality of companies from a user terminal 3. In other respects, it is configured in the same way as the first extraction unit 101, and therefore detailed description will not be repeated.

The second extraction unit 12 is configured in the same manner as the second extraction unit 102 in exemplary embodiment 1, and therefore a detailed description will not be repeated.

The output unit 13 differs from the output unit 103 in exemplary embodiment 1 in that the output unit 13 outputs information indicating the matching case to the user terminal 3. Specifically, the output unit 13 transmits information indicating the matching case to the user terminal 3. In other respects, the output unit 13 is configured in the same way as the output unit 103, and therefore detailed description will not be repeated.

(Configuration of user terminal)
3, the user terminal 3 includes an input unit 31 and a display unit 32. The input unit 31 is configured to realize an input means in this exemplary embodiment. The display unit 32 is configured to realize a display means in this exemplary embodiment. The user terminal 3 is connected to the input device and the display device (neither of which are shown).

The input unit 31 acquires input information indicating a target company among a plurality of companies via an input device. The input unit 31 transmits the acquired input information to the case output device 10.

The display unit 32 displays information indicating the matching examples output by the example output device 10 on a display device.
<Flow of example output method>
The flow of the case example output method S10 executed by the case example output system 1 configured as above will be described with reference to Fig. 4. Fig. 4 is a flow diagram showing the flow of the case example output method S10. As shown in Fig. 4, the case example output method S10 includes steps S11 to S15.

(Step S11)
In step S<b>11 , the input unit 31 of the user terminal 3 acquires input information indicating a target company among a plurality of companies, and transmits the acquired input information to the case example output device 10 .

(Step S12)
In step S12, the first extraction unit 11 refers to a storage device in which the collaboration desire information of each of the multiple companies is stored, and extracts from the multiple companies a first company that has a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company indicated by the input information.

(Step S13)
In step S13, the second extraction unit 12 extracts, from among the multiple companies, a second company having a collaboration desire similar to the collaboration desire of the first company, based on the collaboration desire information of the first company.

(Step S14)
In step S14, the output unit 13 outputs a matching example related to the collaboration content between the first company and the second company. Specifically, the output unit 13 transmits matching example information indicating the matching example to the user terminal 3.

(Step S15)
In step S15, the display unit 32 of the user terminal 3 displays the matching case information transmitted by the case output device 10 on the display device.

<Advantages of this exemplary embodiment>
With the above-described configuration, according to the case example output system 1 of this exemplary embodiment, a user of a user terminal can input input information indicating a target company and thereby grasp on the display screen highly useful matching cases that can be useful in business matching with the target company.

Exemplary embodiment 3
A third exemplary embodiment of the present invention will be described in detail with reference to the drawings. Note that components having the same functions as those described in the first and second exemplary embodiments are given the same reference numerals, and the description thereof will not be repeated.

<Configuration of the case example output system>
The configuration of the case example output system 1A according to this exemplary embodiment will be described with reference to Fig. 5. Fig. 5 is a block diagram showing the configuration of the case example output system 1A. The case example output system 1A is a system that references the needs statement of each company and outputs information indicating matching cases between companies that can serve as a reference for business matching of target companies designated by a user. The needs statement of a company is a statement expressing the needs of the company, and is an example of collaboration request information related to this specification.

As shown in FIG. 5, the case example output system 1A includes a case example output device 10A and a user terminal 3A. The case example output device 10A and the user terminal 3A are communicatively connected via a network N1. Note that, although one user terminal 3A is shown in FIG. 5, the number of user terminals 3A to which the case example output device 10A is connected is not limited. The network N1 is, for example, a wireless LAN (Local Area Network), a wired LAN, a WAN (Wide Area Network), a public line network, a mobile data communication network, or a combination of these networks. However, the configuration of the network N1 is not limited to these.

(Configuration of user terminal)
As shown in FIG. 5, the user terminal 3A includes a communication unit 33A in addition to the same configuration as the user terminal 3 in the second exemplary embodiment.

The communication unit 33A transmits and receives information to and from the case example output device 10A via the network N1. Hereinafter, the communication unit 33A transmitting and receiving information to and from the case example output device 10A will also be described simply as the user terminal 3A transmitting and receiving information to and from the case example output device 10A.

(Configuration of the case example output device)
5, the case example output device 10A includes a control unit 110A, a storage unit 120A, and a communication unit 130A. The control unit 110A includes a first extraction unit 11A, a second extraction unit 12A, and an output unit 13A. The first extraction unit 11A is configured to realize a first extraction means in this exemplary embodiment. The second extraction unit 12A is configured to realize a second extraction means in this exemplary embodiment. The output unit 13A is configured to realize an output means in this exemplary embodiment. Details of these functional blocks included in the control unit 110A will be described later.

The storage unit 120A stores a needs information database DB1 and a case database DB3. Details of the needs information database DB1 and the case database DB3 will be described later. The storage unit 120A is configured to realize a storage device in this exemplary embodiment.

The communication unit 130A transmits and receives information to and from the user terminal 3A via the network N1 under the control of the control unit 110A. Hereinafter, the transmission and reception of information between the control unit 110A and the user terminal 3A via the communication unit 130A will also be simply referred to as the control unit 110A transmitting and receiving information to and from the user terminal 3A.

(Needs information database)
The configuration of the needs information database DB1 will be described with reference to Fig. 6. Fig. 6 is a diagram showing a specific example of the needs information database DB1. As shown in Fig. 6, the needs information database DB1 stores information including a needs statement for each of a plurality of companies. The needs statement for each company in this exemplary embodiment is an example of the "collaboration desire information" set forth in the claims.

The needs statement of each company includes, for example, a phrase that indicates the characteristics of a partner that the company is looking for. For example, in Figure 6, the phrase "We are looking for a manufacturer of processed foods for gifts" included in the needs statement of company A indicates an example of a characteristic of a partner that company A is looking for. Also, for example, in Figure 6, the phrase "We are looking for a sales channel for freeze-dried foods" included in the needs statement related to company B indicates an example of a characteristic of a partner that company B is looking for.

(Companies that have registered a statement of needs)
Hereinafter, a company whose information including a needs statement is stored in the needs information database DB1 will be referred to as a "company whose needs statement is registered in the needs information database DB1" or simply as a "company whose needs statement is registered." A new company's needs statement may be added and registered after the case example output device 10A starts operating. Also, an already registered needs statement may be modified after the case example output device 10A starts operating. Also, an already registered company's needs statement may be deleted after the case example output device 10A starts operating.

(multiple companies)
"Multiple companies" refers to multiple companies whose needs statements are registered in the needs information database DB1.

(Target companies)
The term "target company" refers to a company that is a target of matching among a plurality of companies. The target company is designated by, for example, a user of the case example output device 10A.

(First company)
The "first company" refers to a company that has a similar collaboration desire to that of the target company. As an example, the first company is a company that the case example output device 10A recommends as a collaboration partner for the target company, that is, a company that is recommended as a matching candidate for the target company. Note that the first company is not limited to a company that is recommended as a collaboration partner for the target company.

(Second company)
A "second company" refers to a company that has collaboration aspirations similar to those of the first company.

(Candidate companies)
A "candidate company" refers to a company among multiple companies other than the target company. A candidate company is a company that is a candidate for the first company. There are one or more candidate companies for one target company. In the following explanation, for convenience of explanation, when there is no need to distinguish between the target company, the first company, and the candidate company, they are also simply referred to as "companies."

(Case Database)
The configuration of the case database DB3 will be described with reference to FIG. 7. FIG. 7 is a diagram showing a specific example of the case database DB3. As shown in FIG. 7, the case database DB3 stores matching cases of companies. The matching cases include information indicating multiple companies that have collaborated or multiple companies that are scheduled to collaborate. The matching cases also include information indicating the degree of matching between the companies. The information indicating the degree of matching includes, for example, information on how far the collaboration has progressed, information on how far the negotiations have progressed, or information that numerically represents the degree of success of collaboration between the companies. The matching case information may also include other information, such as information indicating the time of collaboration.

In the example of Figure 7, the matching case information stored in the case database DB3 has the following items associated with each other: "Company combination," "Collaboration content," and "Recommendation level." Of these items, the "Company combination" item stores information indicating the companies in the matching case. The information stored in this item may be information indicating two companies, or may be information indicating three or more companies.

The "Collaboration Content" item stores information indicating the specific content of the collaboration in the matching case. The "Recommendation Level" item stores information indicating the degree of matching in the matching case. For example, if the collaboration is successful, the recommendation level is high, and if the collaboration is unsuccessful, the recommendation level is low. The recommendation level may be set in advance, for example, by an administrator of the case output device 10A, or may be determined by the case output device 10A (or another device) based on information indicating the performance of the companies, etc. The case output device 10A may, for example, calculate the recommendation level so that the higher the growth rate of performance before and after the collaboration, the higher the recommendation level.

Each item in the case database DB3 is registered, for example, by an administrator of the case output device 10A.

(Configuration of the First Extraction Unit)
The first extraction unit 11A extracts one or more first companies having a collaboration request similar to the collaboration request of the target company from among a plurality of companies, using the needs statements of the companies stored in the needs information database DB1. The method of extracting the first companies will be described in detail later.

(Configuration of the second extraction unit)
The second extraction unit 12A refers to the needs information database DB1 and extracts, from the plurality of companies, one or more second companies having a collaboration desire similar to the collaboration desire of the first company specified based on the target company. The method of extracting the second companies will be described in detail later.

(Output section configuration)
The output unit 13A outputs a matching example related to the collaboration content between the first company and the second company. For example, the output unit 13A outputs matching example information indicating the matching example by transmitting it to the user terminal 3A.

<Flow of example output method>
The flow of the case example output method S10A executed by the case example output system 1A configured as above will be described with reference to Fig. 8. Fig. 8 is a flow diagram showing the flow of the case example output method S10A. As shown in Fig. 8, the case example output method S10A includes steps S101 to S108.

(Step S101)
In step S101, the input unit 31 of the user terminal 3A acquires input information via an input device. The input information is information indicating a target company, for example, identification information for identifying the target company. The input information is input, for example, by a user of the user terminal 3A operating the input device. For example, the user may input identification information indicating the target company using the input device, or may input the input information by performing an operation to specify the target company from among multiple companies using the input device.

(Step S102)
In step S102, the input unit 31 transmits the acquired input information to the case example output device 10A. The first extraction unit 11A receives the input information via the communication unit 130A.

(Step S103)
In step S103, the first extraction unit 11A refers to the needs sentences of each company and extracts one or more candidate companies whose needs sentences are similar to those of the target company indicated by the input information as first companies. Specific examples of the method by which the first extraction unit 11A determines the similarity between the needs sentences include (a) a method based on the distance between words, (b) a method based on the distance between documents, or (c) a method based on a learning model. Details of these methods are described below. However, the method of determining the similarity between the needs sentences is not limited to these.

(a: Method based on distance between words)
When using this method, the first extraction unit 11A calculates the similarity between the needs sentences of the target company and each candidate company based on the word distance. Specifically, the first extraction unit 11A calculates the word distance for each combination between each word included in the needs sentence of the target company and each word included in the needs sentence of the candidate company. In addition, the first extraction unit 11A calculates the similarity between the needs sentences of the target company and each candidate company using the calculated word distance.

For example, the first extraction unit 11A calculates the word distance for each combination of a word w1i (i = 1, 2, ..., n) included in the needs sentence of the target company and a word w2j (j = 1, 2, ..., m) included in the needs sentence of the candidate company. Here, n and m are natural numbers. In this case, there are n x m combinations between the words w1i and w2j. In other words, the first extraction unit 11A calculates n x m word distances. Here, when the characteristics of each word w1i and w2j are expressed as a vector, the word distance can be expressed by the angle between the two vectors or the Euclidean distance between the vectors. As a technique for expressing the characteristics of a word as a vector, it is possible to use a learning model that has been machine-learned to input a word and output a feature vector. As such a learning model, a technique such as word2vec can be applied, but is not limited to this.

The first extraction unit 11A calculates the similarity between the needs sentences of the target company and the candidate company using the statistical value of the distance between words. As a specific example, the first extraction unit 11A calculates the similarity so that the smaller the average value of the distance between words of all combinations of words w1i and w2j, the larger the similarity. As another specific example, the first extraction unit 11A calculates the similarity so that the smaller the average value of the distance between words of a predetermined number of all combinations, starting from the one with the shortest distance between words, the larger the similarity.

The first extraction unit 11A identifies, as the first company, one or more candidate companies whose calculated similarity satisfies a predetermined condition. As an example, the first extraction unit 11A identifies, as the first company, one or more candidate companies whose similarity is equal to or greater than a threshold. The first extraction unit 11A may also identify, as the first company, a predetermined number of candidate companies in descending order of similarity.

(b: Method based on document distance)
When this method is used, the first extraction unit 11A calculates the similarity between the needs statements of the target company and each candidate company based on the inter-document distance, and extracts one or more candidate companies whose similarity is equal to or greater than a threshold as first companies.

Here, when the features of each need sentence are expressed as a vector, the inter-document distance between the need sentences can be expressed by the angle between the two vectors or the Euclidean distance between the vectors. A possible technique for expressing the features of the need sentence as a vector is to use a learning model that has been machine-learned to input the need sentence and output a feature vector. As such a learning model, a technique such as doc2vec can be applied, but is not limited to this. The first extraction unit 11A calculates the similarity so that it increases as the inter-document distance decreases.

The first extraction unit 11A identifies, as the first company, one or more candidate companies whose calculated similarity satisfies a predetermined condition. As an example, the first extraction unit 11A identifies, as the first company, one or more candidate companies whose similarity is equal to or greater than a threshold. The first extraction unit 11A may also identify, as the first company, a predetermined number of candidate companies in descending order of similarity.

When determining similarity using the above method (a) or (b), in other words, the first extraction unit 11A identifies the first company using the distance between the collaboration desire information of the target company and each of the collaboration desire information of the multiple companies in a specified feature space. The distance between the collaboration desire information of the companies is, for example, the statistical value of the distance between words in (a) or the distance between documents in (b). The specified feature space is, for example, a Euclidean space in which the features of words or documents are expressed as vectors.

(c: Method based on learning model)
When using this method, the first extraction unit 11A uses a learning model that has been trained by machine learning to input the needs statements of two companies and output information indicating the similarity between the needs statements. The first extraction unit 11A inputs the needs statements of the target company and the needs statements of the candidate companies into the learning model. The first extraction unit 11A also extracts one or more companies for which "information indicating similarity" has been output from the learning model as the first company.

For example, the first extraction unit 11A generates a learning model in advance by machine learning as follows. The first extraction unit 11A trains the learning model so that, using the needs sentences of two companies among a plurality of companies that have actual matching cases as teacher data, information indicating that the needs sentences are similar is output when these needs sentences are input. Also, for example, the first extraction unit 11A trains the learning model so that, when the needs sentences of two companies that do not have matching cases are input, information indicating that the needs sentences are not similar is output. As an example, the first extraction unit 11A may generate a learning model by performing transfer learning or fine tuning using a pre-trained model. Specific examples of pre-trained models include, but are not limited to, BERT (Bidirectional Encoder Representations from Transformers). Note that the learning model may have been trained to output a similarity instead of outputting information indicating whether or not the two companies are similar. In this case, the first extraction unit 11A extracts one or more candidate companies that output a similarity equal to or greater than a threshold as the first company.

In this case, the first extraction unit 11A identifies, as the first company, one or more candidate companies whose output similarity satisfies a predetermined condition. As an example, the first extraction unit 11A identifies, as the first company, one or more candidate companies whose similarity is equal to or greater than a threshold. The first extraction unit 11A may also identify, as the first company, a predetermined number of candidate companies in descending order of similarity.

(Step S104)
In step S104, the second extraction unit 12A identifies a company from the first company for extracting the second company. The company from which the second company is extracted is also referred to as an "extraction company" below. For example, the second extraction unit 12A identifies a company from the first company that satisfies a predetermined condition as an extraction company. The predetermined condition is, for example, a condition that the distance between the target company and the needs statement is the smallest. In other words, the second extraction unit 12A identifies an extraction company from one or more companies extracted by the first extraction unit 11A using the distance between the collaboration request information of the target company and the collaboration request information of the first company extracted by the first extraction unit 11A in the feature space.

As another example, the second extraction unit 12A may randomly identify companies to be extracted from among the first companies. The method by which the second extraction unit 12A identifies companies to be extracted is not limited to the above-mentioned method and may be another method.

In addition, the second extraction unit 12A may, for example, identify the companies to be extracted using a method different from the method by which the first extraction unit 11A extracts the first company. For example, the first extraction unit 11A may extract the first company using the above-mentioned (a) method based on word distance, while the second extraction unit 12A may identify the companies to be extracted using the above-mentioned (c) method based on the learning model. In this way, the method by which the second extraction unit 12A identifies the companies to be extracted may be the same as the method by which the first extraction unit 11A extracts the first company, or may be a different method.

(Step S105)
In step S105, the second extraction unit 12A refers to the needs sentences of each company and extracts a second company from among the multiple companies. For example, the second extraction unit 12A refers to the needs sentences of each company and extracts, from among the multiple candidate companies, a company whose needs sentence is similar to the needs sentence of the extraction company as the second company. A specific example of the method by which the second extraction unit 12A determines the similarity between needs sentences is the same as the method described in step S103 above. That is, specific examples of the method by which the second extraction unit 12 determines the similarity between needs sentences include (a) a method based on word distance, (b) a method based on document distance, or (c) a method based on a learning model. The details of these methods have been described above, so the description will not be repeated.

When determining similarity using the above method (a) or (b), in other words, the second extraction unit 12A identifies the second company based on the distance between the collaboration desire information of the first company and each of the collaboration desire information of the multiple companies in a specified feature space. The distance between the collaboration desire information of the companies is, for example, the statistical value of the distance between words in (a) or the distance between documents in (b). The specified feature space is, for example, a Euclidean space in which the features of words or documents are expressed as vectors.

The method by which the second extraction unit 12A extracts the second company may be the same as or different from the method by which the first extraction unit 11A extracts the first company. For example, the first extraction unit 11A may extract the first company using the method based on the word distance (a) above, while the second extraction unit 12A may extract the second company using the method based on the word distance (a) above, using the companies for extraction identified using the method based on the learning model (c) above.

(Step S106)
In step S106, the output unit 13A searches for matching examples between a first company and a second company from the case database DB3. For example, the output unit 13A identifies a plurality of combinations of a first company and a second company, and searches for matching examples from the case database DB3 using the identified combinations of companies as a key.

(Step S107)
In step S107, the output unit 13A generates matching case information representing the matching case that is the search result of step S106, and outputs the generated matching case information by transmitting it to the user terminal 3A. Specifically, the output unit 13A generates screen data representing the matching case, for example, and transmits the generated screen data to the user terminal 3A. The contents of the screen represented by the screen data will be described later. The user terminal 3A receives the screen data transmitted by the output unit 13A.

(Step S108)
In step S108, the display unit 32 of the user terminal 3A displays the matching example indicated by the matching example information on the display device. Specifically, the display unit 32 displays a screen represented by the screen data received from the example output device 10A on the display device. For example, the display unit 32 displays the matching examples in a display mode based on the recommendation level. Displaying in a display mode based on the recommendation level includes, for example, sorting and displaying a plurality of matching examples by the recommendation level, displaying information representing the matching examples in different colors or shapes depending on the recommendation level, and displaying a figure (graph, etc.) representing the recommendation level of each matching example. An example of a screen displayed on the user terminal 3A in this step will be described below.

<Screen example>
9 is a screen example G11 that displays a matching example. In the example of FIG. 9, the screen example G11 includes a list L11 that includes a plurality of matching examples. Each matching example in the list L11 includes a combination of a plurality of companies, collaboration details, and a figure that represents the matching success degree of each matching example. The matching success degree is information that indicates the degree of matching. The matching success degree may be the same as the recommendation degree, or the output unit 13A may calculate the matching success degree from the recommendation degree. The matching success degree may be, for example, a numerical value between 0 and 100 that represents the degree of matching.

The display unit 32 displays a figure representing the matching success rate for each matching case in the screen example G11. The figure representing the matching success rate is not limited to the one exemplified in FIG. 9 and may be another figure. The figure representing the matching success rate may be, for example, a pie chart or a bar graph representing the matching success rate.

Furthermore, the display unit 32 displays the matching cases in the example screen G11 sorted in descending or ascending order of the matching success rate. In other words, the output unit 13A generates screen data representing a screen including a list in which the matching cases are sorted in descending or ascending order of the matching success rate.

By displaying the matching examples on screen example G11, the user can recognize the matching examples related to the target company that the user specified. In addition, by displaying the matching examples on screen example G11 sorted by the matching success rate, the user can easily grasp the more useful matching examples.

<Advantages of this exemplary embodiment>
As described above, according to this exemplary embodiment, the case example output system 1A outputs not only matching cases of the target company but also matching cases of companies similar to the target company. This makes it easy for the case example output system 1A to grasp matching cases with high usefulness.

Exemplary embodiment 4
A fourth exemplary embodiment of the present invention will be described in detail with reference to the drawings. Note that components having the same functions as those described in the first to third exemplary embodiments are given the same reference numerals, and the description thereof will not be repeated.

<Configuration of the case example output system>
The case example output system 1B according to this exemplary embodiment is a modified version of the exemplary embodiment 3. The case example output system 1B selects a second company from among companies that are unlikely to compete with the target company. The configuration of the case example output system 1B will be described with reference to Fig. 10. Fig. 10 is a block diagram showing the configuration of the case example output system 1B.

As shown in Figure 10, the case example output system 1B is configured in a manner similar to that of the case example output system 1A according to the exemplary embodiment 3, except that the case example output system 1B includes a case example output device 10B instead of the case example output device 10A. In other respects, the case example output system 1B is configured in a manner similar to that of the case example output system 1A.

(Configuration of the case example output device)
As shown in FIG. 10, a case example output device 10B includes a control unit 110B, a storage unit 120B, and a communication unit 130A.

The control unit 110B is configured in a manner similar to that of the control unit 110A in the exemplary embodiment 3, except that the control unit 110B includes a second extraction unit 12B instead of the second extraction unit 12A. In other respects, the control unit 110B is configured in a manner similar to that of the control unit 110A.

In addition to being configured similarly to memory unit 120A in exemplary embodiment 3, memory unit 120B further includes a corporate information database DB2.

(Corporate information database)
The configuration of the company information database DB2 will be described with reference to FIG. 11. FIG. 11 is a diagram showing a specific example of the company information database DB2. The company information database DB2 is a database in which the industries of a plurality of companies are registered. As shown in FIG. 11, the company information database DB2 stores company information on each of a plurality of companies. For example, the company information includes information indicating the industry. In the example of FIG. 11, information indicating the industry "information and communications" is stored as the company information of companies A, I, J, and K. Furthermore, information indicating the industry "pharmaceutical manufacturing" is stored as the company information of company H. Furthermore, information indicating the industry "chemical product wholesale" is stored as the company information of company L. Note that the company information may include other information related to the company instead of or in addition to the information indicating the industry.

The second extraction unit 12B refers to the company information of each of the multiple companies stored in the company information database DB2 and selects a second company from among companies other than the competitors of the target company. A competitor is a company that is likely to compete with the target company. Competitors include, for example, companies in the same industry as the target company or companies in a similar industry to the target company. Details of the selection process will be described later.

<Flow of example output method>
The flow of the case example output method S10B executed by the case example output system 1B configured as above will be described with reference to Fig. 12. Fig. 12 is a flow diagram showing the flow of the case example output method S10B. As shown in Fig. 12, the case example output method S10B is configured almost similarly to the case example output method S10A in the exemplary embodiment 3, but differs in that it includes steps S105a to S105b instead of step S105. Steps S105a to S105b will be described below. The other steps are similar to those of the case example output method S10A, and therefore detailed description will not be repeated.

(Step S105a)
In step S105a, the second extraction unit 12B of the case example output device 10B refers to the company information database DB2 to identify the second company from among companies other than the competitors of the target company. As an example, the second extraction unit 12B identifies companies in the same industry as the target company as competitors based on the industries of the multiple companies included in the company information. Competitor companies include, for example, companies in the same industry as the target company or companies in a similar industry to the target company.

(Specific example of process for identifying competitors)
As an example, the second extraction unit 12B refers to the company information database DB2 and identifies companies whose industry is the same as that of the target company as competitor companies. For example, in the example of the company information database DB2 shown in Fig. 11, if the target company is company A, the second extraction unit 12B identifies companies I, J, and K whose industry is "information and communications", the same as that of company A, as competitor companies.

Note that the method of identifying competing companies by referring to company information is not limited to this. For example, the second extraction unit 12B may use a learning model that is trained to input the company information of two companies and output the competitiveness. In this case, the second extraction unit 12B inputs the company information of the target company and the company information of the candidate company into the learning model, and identifies the candidate whose output competitiveness is equal to or greater than a threshold as a competing company.

In addition, the second extraction unit 12B may refer to the company information database DB2 to identify companies in an industry similar to that of the target company as competitors. In this case, for example, similar industry information indicating a group of industries that are similar to each other may be stored in advance in the storage unit 120B of the case example output device 10B, and the second extraction unit 12B may use the similar industry information stored in the storage unit 120B to identify companies in an industry similar to that of the target company as competitors.

In step S105b, the second extraction unit 12B selects a second company from among companies excluding competitors of the target company based on the collaboration desire information of the first company.

Thereafter, the case example output system 1B executes steps S106 to S108 to display matching cases on the display device of the user terminal 3A.

<Advantages of this exemplary embodiment>
As described above, according to the present exemplary embodiment, the case example output device 10B does not select, as the second company, a company that is highly likely to compete with the target company even if the company has similar needs statements between the target company and the second company. This allows the case example output device 10B to present to the user matching cases of companies that are unlikely to compete with the target company, i.e., matching cases with higher usefulness.

In the above exemplary embodiment, a configuration has been described in which the needs information database DB1 and the company information database DB2 are separate databases. The database configuration is not limited to that shown in the above embodiment. Needs information and company information may be stored in a single database. In other words, the company information stored in the company information database may include a needs statement and information related to the industry.

Exemplary embodiment 5
A fifth exemplary embodiment of the present invention will be described in detail with reference to the drawings. Note that components having the same functions as those described in the first to fourth exemplary embodiments are given the same reference numerals, and the description thereof will not be repeated.

<Configuration of the case example output system>
The configuration of the case example output system 1C according to this exemplary embodiment will be described with reference to FIG. 13. FIG. 13 is a block diagram showing the configuration of the case example output system 1C. The case example output system 1C is a modified version of the case example output system 3. When extracting the second company, the case example output system 1C extracts a company that is not included in the first company as the second company. In addition, the case example output system 1C displays the matching case example in a display mode different from that of the above-mentioned exemplary embodiment 3. As shown in FIG. 13, the case example output system 1C includes a case example output device 10C instead of the case example output device 10A of the case example output system 1A according to the exemplary embodiment 3.

(Configuration of the case example output device)
The case example output device 10C includes a control unit 110C, a storage unit 120C, and a communication unit 130A. The control unit 110C includes a second extraction unit 12C and an output unit 13C instead of the second extraction unit 12A and the output unit 13A of the control unit 110C.

The second extraction unit 12C extracts the second company from among the companies that have not been extracted as the first company. The output unit 13C outputs information indicating the matching case by transmitting it to the user terminal 3.

The memory unit 120C includes a case database DB31 instead of the case database DB3. The matching case information stored in the case database DB31 includes information indicating multiple companies that have collaborated or will collaborate, and information indicating the degree of matching between the companies, as well as attribute information indicating the attributes of the matching case. The attributes of the matching case are, for example, information indicating whether the matching case is a positive case or a negative case.

<Flow of example output method>
The flow of the case example output method S10C executed by the case example output system 1C configured as above will be described with reference to Fig. 14. Fig. 14 is a flow diagram showing the flow of the case example output method S10C. As shown in Fig. 14, the case example output method S10C includes steps S104c, S105c, S105d, and S107c instead of steps S104, S105, and S107 of the case example output method S10A in the exemplary embodiment 3. Steps S104c, S105c, S105d, and S107c will be described below. The other steps are similar to those of the case example output method S10B, and detailed description will not be repeated.

(Step S104c)
In step S104c, the second extraction unit 12C identifies companies to be extracted based on the user's selection. For example, the second extraction unit 12A generates screen data showing a list of the first companies and transmits it to the user terminal 3A. The user terminal 3A displays the list of the first companies on a display device.

Figure 15 shows a screen example G21 including a list of first companies. As shown in Figure 15, screen example G21 includes a list L21 of the company names of the first companies, Company B, Company C, Company D, Company E, and Company F. When screen example G21 is displayed and the user uses the input device to select one of the first companies, user terminal 3A transmits information representing the selected company to case example output device 10C. Case example output device 10C receives information from user terminal 3A and identifies a company to be extracted based on the received information.

(Step S105c)
In step S105c, the second extraction unit 12C of the case example output device 10C refers to the needs statement of each company and extracts one or more companies from the multiple companies as candidates for the second company. The details of the process in this step in which the second extraction unit 12C extracts candidates for the second company are similar to the process in step S105 in the third exemplary embodiment in which the second extraction unit 12A extracts the second company, and therefore will not be described in detail again.

(Step S105d)
In step S105d, the second extraction unit 12C extracts, from among the candidates for the second company extracted in step S105c, companies other than the companies extracted as the first companies by the first extraction unit 11A, as second companies. In other words, the second extraction unit 12C extracts, from among the second companies, companies that are not included in the first companies extracted by the first extraction unit 11A, as second companies.

(Step S107c)
In step S107c, the output unit 13C generates matching example information representing the matching example that is the search result in step S106, and outputs the generated matching example information by transmitting it to the user terminal 3A.

The output unit 13C generates screen data that displays matching cases by attribute as matching case information to be sent to the user terminal 3A.

<Screen example>
An example of a screen displayed by the case example output device 10C in step S107 will be described with reference to Figs. 16 and 17. Fig. 16 shows a screen example G31 of a matching case. The screen example G31 includes a list L31 of positive matching cases and a list L32 of negative matching cases. In the case of the screen example G31, the output unit 13C generates screen data representing a screen including the list L31 of positive matching cases and the list L33 of negative matching cases. The output unit 13 generates screen data representing the screen illustrated in Fig. 16 based on attribute information included in the matching case information stored in the case database.

Figure 17 shows a screen example G41 of a matching example. Screen example G41 includes a list L41 of multiple matching examples. Each matching example in list L41 includes a combination of multiple companies, collaboration details, and a figure representing the matching success rate of each matching example. In the example of Figure 17, the figure representing the matching success rate is a bar graph representing the matching success rate.

In the example of Figure 17, when a user performs an operation to select a company name included in list L41, the user terminal 3A, for example, transmits information indicating the company selected by the user to the case example output device 10C. In this case, the case example output device 10C receives information from the user terminal 3A and transmits information about the company corresponding to the received information to the user terminal 3A. The information about the company may be, for example, a needs statement about the company stored in the needs information database DB1. The user terminal 3A receives the information about the company from the case example output device 10C and displays the received information on the display device.

<Advantages of this exemplary embodiment>
As described above, according to this exemplary embodiment, the case example output system 1C extracts a company that is not included in the first companies as the second company, which makes it easy to output matching case example information that shows a variety of matching cases.

Furthermore, according to this exemplary embodiment, the case example output system 1C extracts the second company using a company for extraction selected by the user from among the first companies. This makes it easier for the case example output system 1C to output matching cases that are in line with the user's intentions compared to a case in which the user does not select a company for extraction.

[Software implementation example]
A part or all of the functions of the case example output devices 10, 10A, 10B, and 10C may be realized by hardware such as an integrated circuit (IC chip), or may be realized by software.

In the latter case, the case example output devices 10, 10A, 10B, and 10C are realized, for example, by a computer that executes instructions of a program, which is software that realizes each function. An example of such a computer (hereinafter referred to as computer C) is shown in FIG. 18. Computer C has at least one processor C1 and at least one memory C2. Memory C2 stores program P for operating computer C as case example output devices 10, 10A, 10B, and 10C. In computer C, processor C1 reads and executes program P from memory C2, thereby realizing each function of case example output devices 10, 10A, 10B, and 10C.

The processor C1 may be, for example, a central processing unit (CPU), a graphic processing unit (GPU), a digital signal processor (DSP), a micro processing unit (MPU), a floating point number processing unit (FPU), a physics processing unit (PPU), a microcontroller, or a combination of these. The memory C2 may be, for example, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), or a combination of these.

The computer C may further include a RAM (Random Access Memory) for expanding the program P during execution and for temporarily storing various data. The computer C may further include a communications interface for transmitting and receiving data to and from other devices. The computer C may further include an input/output interface for connecting input/output devices such as a keyboard, mouse, display, and printer.

The program P can also be recorded on a non-transitory, tangible recording medium M that can be read by the computer C. Such a recording medium M can be, for example, a tape, a disk, a card, a semiconductor memory, or a programmable logic circuit. The computer C can acquire the program P via such a recording medium M. The program P can also be transmitted via a transmission medium. Such a transmission medium can be, for example, a communications network or broadcast waves. The computer C can also acquire the program P via such a transmission medium.

[Additional Note 1]
The present invention is not limited to the above-described embodiment, and various modifications are possible within the scope of the claims. For example, embodiments obtained by appropriately combining the technical means disclosed in the above-described embodiment are also included in the technical scope of the present invention.

[Additional Note 2]
Some or all of the above-described embodiments can be described as follows. However, the present invention is not limited to the aspects described below.

(Appendix 1)
a first extraction means for extracting, from among the plurality of companies, a first company having a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company, by referring to a storage device in which collaboration desire information of each of the plurality of companies is stored;
a second extraction means for extracting, from the plurality of companies, a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company;
an output means for outputting a matching example regarding the content of collaboration between the first company and the second company;
An example output device comprising:

According to the above configuration, the case example output device outputs information indicating not only matching cases of the target company, but also matching cases of a first company that has a collaboration desire similar to the collaboration desire of the target company. This allows the case example output device to output information indicating highly useful matching cases that can be useful for business matching of the target company.

(Appendix 2)
the output means searches for matching examples between the first company and the second company from a database in which matching examples between companies are stored, and outputs a search result.
2. The case example output device according to claim 1 .

According to the above configuration, the case example output device outputs information indicating matching cases that indicate matching cases searched from a database in which matching cases are stored. This allows the case example output device to output information indicating highly useful matching cases registered in the database that can be useful in business matching for target companies.

(Appendix 3)
The matching examples include information indicating the degree of matching between companies.
3. The case example output device according to claim 2.

According to the above configuration, the case example output device outputs information including information indicating the degree of matching between companies as information indicating matching cases between companies. This allows the case example output device to output information indicating highly useful matching cases that can be useful in business matching for the target companies.

(Appendix 4)
The second extraction means refers to company information of each of the plurality of companies stored in the storage device, and identifies the companies to be extracted from among companies other than competitors of the target company.
2. The case example output device according to claim 1 .

According to the above configuration, the case example output device does not identify, as a company for extraction, a company that is similar to the target company but is likely to be a competitor. Therefore, the case example output device can output information that indicates a more useful matching case than when a company with a high probability of competition is identified as a company for extraction.

(Appendix 5)
The second extraction means identifies, as the competitor companies, companies in the same industry as the target company based on the industries of the plurality of companies included in the company information.
5. The case output device according to claim 4,

According to the above configuration, the case example output device refers to the database and identifies companies in the industry of the target company as competing companies, thereby outputting information indicating matching cases that are more useful than when the extraction company is a competing company.

(Appendix 6)
the first extraction means extracts the first company from among the plurality of companies based on a distance between collaboration desire information of the target company and collaboration desire information of each of the plurality of companies in a predetermined feature space;
6. The case example output device according to claim 1,

According to the above configuration, the case example output device can output information indicating more useful matching cases than when it does not use the distance between sentences to extract companies similar to the target company.

(Appendix 7)
The second extraction means extracts one or more companies from the plurality of companies based on a distance between the collaboration desire information of the extraction company and each of the collaboration desire information of the plurality of companies in a predetermined feature space.
7. The case example output device according to claim 1,

According to the above configuration, the case example output device can output information indicating more useful matching cases than when it does not use the distance between sentences to extract companies similar to the extraction company.

(Appendix 8)
The second extraction means extracts the second company from among companies that have not been extracted as the first company.
8. The case example output device according to claim 1,

According to the above configuration, the case example output device can output information showing a wider variety of matching cases than when the case example output device does not extract companies other than companies similar to the target company as companies similar to the extraction company.

(Appendix 9)
The case output device is
Refer to a storage device in which collaboration desire information of each of a plurality of companies is stored, and extract a first company having a collaboration desire similar to the collaboration desire of the target company from among the plurality of companies based on the collaboration desire information of the target company;
Extracting a second company having a collaboration desire similar to the collaboration desire of the first company from among the multiple companies based on the collaboration desire information of the first company;
outputting a matching example regarding collaboration content between the first company and the second company;
23. A method for outputting cases comprising:

The above configuration achieves the same effect as in Appendix 1.

(Appendix 10)
A program for causing a computer to function as a case output device,
The program causes the computer to
a first extraction means for extracting, from among the plurality of companies, a first company having a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company, by referring to a storage device in which collaboration desire information of each of the plurality of companies is stored;
a second extraction means for extracting, from the plurality of companies, a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company;
and outputting a matching example relating to the content of collaboration between the first company and the second company.
A program characterized by:

The above configuration achieves the same effect as in Appendix 1.

(Appendix 11)
A storage medium storing a program for causing a computer to function as a case example output device,
The program causes the computer to
a first extraction means for extracting, from among the plurality of companies, a first company having a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company, by referring to a storage device in which collaboration desire information of each of the plurality of companies is stored;
a second extraction means for extracting, from the plurality of companies, a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company;
and outputting a matching example relating to the content of collaboration between the first company and the second company.
A storage medium storing a program characterized by:

The above configuration achieves the same effect as in Appendix 1.

(Appendix 12)
A case output device and a user terminal,
The example output device includes:
a first extraction means for extracting, from among the plurality of companies, a first company having a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company indicated by the input information, by referring to a storage device in which collaboration desire information of each of the plurality of companies is stored;
a second extraction means for extracting, from the plurality of companies, a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company;
and an output means for outputting a matching example relating to the content of collaboration between the first company and the second company,
The user terminal,
An input means for acquiring the input information;
and a display means for displaying information indicating the matching examples output by the example output device.
A case output system comprising:

The above configuration achieves the same effect as in Appendix 1.

[Additional Note 3]
A part or all of the above-described embodiments can be further expressed as follows.

At least one processor, the processor comprising:
a first extraction process for extracting, from among the plurality of companies, a first company having a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company by referring to a storage device in which collaboration desire information of each of the plurality of companies is stored;
a second extraction process for extracting, from the plurality of companies, a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company;
An output process of outputting a matching example regarding collaboration content between the first company and the second company;
A case output device that executes the above.

The case example output device may further include a memory, and the memory may store a program for causing the processor to execute the first extraction process, the second extraction process, and the output process. The program may also be recorded on a computer-readable, non-transitory, tangible recording medium.

10, 10A, 10B, 10C, 10D, 100 Case example output device 1, 1A, 1B, 1C, 1D Case example output system 3, 3A User terminal 11, 11A, 101 First extraction unit 12, 12A, 12B, 12C, 102 Second extraction unit 13, 13A, 13C, 103 Output unit 31 Input unit 32 Display unit

Claims (9)

a first extraction means for extracting, from among the plurality of companies, a first company having a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company, by referring to a storage device in which collaboration desire information of each of the plurality of companies is stored;
a second extraction means for extracting, from the plurality of companies, a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company;
an output means for outputting a matching example regarding the content of collaboration between the first company and the second company;
Equipped with
The output means searches for a matching example between the first company and the second company from a database in which matching examples between companies are stored, and outputs a search result.
13. A case output device comprising: The matching examples include information indicating the degree of matching between companies.
2. The case output device according to claim 1, wherein: the second extraction means refers to company information of each of the plurality of companies stored in the storage device, and identifies the second company from among companies other than competitors of the target company;
2. The case output device according to claim 1, wherein: The second extraction means identifies, as the competitor companies, companies in the same industry as the target company based on the industries of the plurality of companies included in the company information.
4. The case output device according to claim 3. the first extraction means extracts the first company from among the plurality of companies by using a distance between the collaboration desire information of the target company and each of the collaboration desire information of the plurality of companies in a predetermined feature space;
5. The case example output device according to claim 1, the second extraction means extracts the second company from among the plurality of companies based on a distance between the collaboration desire information of the first company and each of the collaboration desire information of the plurality of companies in a predetermined feature space;
6. The case example output device according to claim 1, The second extraction means extracts the second company from among companies that have not been extracted as the first company.
7. The case example output device according to claim 1, The case output device is
Refer to a storage device in which the collaboration desire information of each of the multiple companies is stored, and based on the collaboration desire information of the target company, select a first company having a collaboration desire similar to the collaboration desire of the target company;
Select from the plurality of companies,
Extracting a second company having a collaboration desire similar to the collaboration desire of the first company from among the multiple companies based on the collaboration desire information of the first company;
Outputting a matching example regarding collaboration content between the first company and the second company;
In the step of outputting the matching example, the example output device searches for a matching example between the first company and the second company from a database in which matching examples between companies are stored, and outputs a search result.
23. A method for outputting cases comprising: A program for causing a computer to function as a case output device,
The program causes the computer to
a first extraction means for extracting, from among the plurality of companies, a first company having a collaboration desire similar to the collaboration desire of the target company based on the collaboration desire information of the target company, by referring to a storage device in which collaboration desire information of each of the plurality of companies is stored;
a second extraction means for extracting, from the plurality of companies, a second company having a collaboration desire similar to the collaboration desire of the first company based on the collaboration desire information of the first company;
an output unit that outputs a matching example regarding the content of a collaboration between the first company and the second company;
the output means searches for matching examples between the first company and the second company from a database in which matching examples between companies are stored, and outputs a search result.
A program characterized by:

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