CN114862214A

CN114862214A - Quantitative evaluation method and device for inter-enterprise cooperation intention

Info

Publication number: CN114862214A
Application number: CN202210527499.6A
Authority: CN
Inventors: 刘爽; 张琴
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2022-05-16
Filing date: 2022-05-16
Publication date: 2022-08-05

Abstract

The invention relates to the technical field of data processing, in particular to a quantitative evaluation method and device for inter-enterprise cooperation intention. The method comprises the steps of obtaining a plurality of primary products of a primary matching enterprise and a plurality of secondary matching enterprises; calculating matching degree scores between a plurality of main products of the secondary matching enterprises and main products of the main matching enterprises through a natural language recognition algorithm, wherein the numerical value of the matching degree score is between 0 and 1; sorting the matching degree scores corresponding to a plurality of main marketing products of the secondary matching enterprise in a descending order; calculating a first score of the intention of collaboration according to the descending order; and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the intention of cooperation first score. By the embodiment of the invention, the problems that the workload for analyzing the cooperation possibility between the to-be-cooperated enterprise and the target cooperation enterprise by using the manual experience is large, the efficiency is low, and the manual experience cannot quantitatively analyze the cooperation possibility between the enterprises, so that a certain error exists in the analysis result are solved.

Description

Quantitative evaluation method and device for inter-enterprise cooperation intention

Technical Field

The invention relates to the technical field of data processing, in particular to a quantitative evaluation method and device for inter-enterprise cooperation intention.

Background

This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.

With the rapid development of economy, the cooperation among enterprises is more and more frequent, in order to save negotiation cost, the enterprise to be cooperated needs to analyze the self-selected target cooperation enterprise in advance to determine the possibility of cooperation between the enterprise to be cooperated and the target cooperation enterprise, and if the possibility is high, the enterprise to be cooperated can carry out cooperation negotiation with the target cooperation enterprise.

In the prior art, the cooperation possibility between the enterprise to be cooperated and the target cooperative enterprise can be analyzed only by using manual experience, for example, the competitiveness (for example, product price, product quality and the like) between a main operation product of the currently cooperated enterprise of the target cooperative enterprise and a main operation product of the enterprise to be cooperated is analyzed, the analysis workload is huge, the efficiency is low, and the manual experience cannot quantitatively analyze the cooperation possibility between the enterprises, so that a certain error exists in an analysis result.

At present, a quantitative evaluation method for inter-enterprise cooperation intention is needed urgently, so that the problems that in the prior art, the workload for analyzing the cooperation possibility between the enterprise to be cooperated and the target cooperation enterprise by using manual experience is large, the efficiency is low, and the manual experience cannot quantitatively analyze the cooperation possibility between the enterprises, so that certain errors exist in an analysis result are solved.

Disclosure of Invention

In order to solve the problems in the prior art, the embodiment of the invention provides a quantitative evaluation method and a quantitative evaluation device for inter-enterprise cooperation intention, which abandons a method for analyzing the cooperation possibility between an enterprise to be cooperated and a target cooperation enterprise by adopting artificial experience, and solves the problems that the workload for analyzing the cooperation possibility between the enterprise to be cooperated and the target cooperation enterprise by utilizing the artificial experience is large, the efficiency is low, and the artificial experience cannot quantitatively analyze the cooperation possibility between the enterprises, so that certain errors exist in an analysis result.

In order to solve the technical problems, the specific technical scheme of the invention is as follows:

in one aspect, an embodiment of the present invention provides a method for quantitatively evaluating inter-enterprise cooperation intention, where the method includes:

acquiring a plurality of primary operation products of a primary matching enterprise and a secondary matching enterprise, wherein the demand type of the primary operation products of the primary matching enterprise and the demand type of the plurality of primary operation products of the secondary matching enterprise can achieve cooperation;

calculating matching degree scores between a plurality of main products of the secondary matching enterprises and main products of the main matching enterprises through a natural language recognition algorithm, wherein the numerical value of the matching degree score is between 0 and 1;

sorting the matching degree scores corresponding to a plurality of main marketing products of the secondary matching enterprise in a descending order;

according to the formula:

calculating an intention of collaboration first score, wherein S represents the intention of collaboration first score, S ₁ Representing the first-ranked match score, S, in the descending order ₂ Representing the degree of match score, S, ranked second in the descending order ₃ Representing the degree of match score, S, ranked second in the descending order _n-2 Representing the matchedness score, S, of the n-2 th rank in the descending order _n-1 Representing the matchedness score, S, of the n-1 th rank in the descending order _n Representing the matchability score for the nth rank in the descending order;

and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the intention of cooperation first score.

Further, calculating a matching degree score between the plurality of primary products of the secondary matching business and the primary products of the primary matching business through a natural language recognition algorithm further comprises,

analyzing the main business products of the main matching enterprises through a natural language recognition algorithm to obtain a first matching word set and a second matching word set of the main business products of the main matching enterprises;

and performing similarity matching on the primary operation product of the secondary matching enterprise and the first matching word set or the second matching word set of the primary operation product of the primary matching enterprise, and calculating a matching degree score between the primary operation product of the secondary matching enterprise and the primary operation product of the primary matching enterprise according to a similarity matching result.

Further, performing similarity matching on the primary operation product of the secondary matching enterprise and the first matching word set or the second matching word set of the primary operation product of the primary matching enterprise, and calculating a matching degree score between the primary operation product of the secondary matching enterprise and the primary operation product of the primary matching enterprise according to a similarity matching result further comprises,

performing first similarity matching on a primary operation product of the secondary matching enterprise and a first matching word set of the primary operation product of the primary matching enterprise;

if the first similarity matching is successful, the matching degree score is a first preset value;

if the first similarity matching is not successful, performing second similarity matching on the primary operation product of the secondary matching enterprise and a second matching word set of the primary operation product of the primary matching enterprise;

and if the second similarity matching is successful, the matching score is a second preset value.

Further, if the second similarity match is not successful, the method further comprises,

analyzing the main business products of the main matching enterprise through a natural language recognition algorithm to obtain a third matching word set, a fourth matching word set and a fifth matching word set of the main business products of the main matching enterprise;

respectively carrying out third similarity matching, fourth similarity matching and fifth similarity matching on the main operation products of the secondary matching enterprises and the third matching word set, the fourth matching word set and the fifth matching word set of the main matching enterprise to respectively obtain matching degree scores corresponding to the third similarity matching, the fourth similarity matching and the fifth similarity matching;

selecting the maximum value of the matching degree scores corresponding to the third similarity matching, the fourth similarity matching and the fifth similarity matching as the matching degree score;

the third similarity matching comprises the step of carrying out third similarity matching on a main camp product of the secondary matching enterprise and a third matching word set of the main camp product of the main matching enterprise, wherein if the matching is successful, the matching score corresponding to the third similarity matching is a third preset value;

the fourth similarity matching comprises the step of carrying out fourth similarity matching on a main business product of the secondary matching enterprise and a fourth matching word set of the main business product of the main matching enterprise, wherein if the matching is successful, the matching score corresponding to the fourth similarity matching is a fourth preset value;

the fifth similarity matching comprises the step of performing fifth similarity matching on a main camp product of the secondary matching enterprise and a fifth matching word set of the main camp product of the main matching enterprise, and if the matching is successful, the matching score corresponding to the fifth similarity matching is a fifth preset value.

Further, before obtaining a plurality of primary products of a primary matching enterprise and a secondary matching enterprise, the method further comprises obtaining a matching enterprise range of the primary matching enterprise;

calculating enterprise range scores of the primary matching enterprise and the secondary matching enterprises according to the matching enterprise ranges and the secondary matching enterprises;

calculating an intention of collaboration second score according to the enterprise-wide score and the intention of collaboration first score;

and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the second intention of cooperation score.

Further, calculating a business-wide score for the primary and secondary matching businesses based on the matching business range and the secondary matching business further comprises,

comparing the secondary matching enterprise with the matching enterprise range to determine a target matching enterprise range to which the secondary matching enterprise belongs;

and taking the preset score of the target matching enterprise range as the enterprise range score.

Further, calculating an intent-to-collaborate second score based on the business-wide score and the intent-to-collaborate first score further comprises,

and calculating the sum of the enterprise range score and the first cooperative score according to a preset weight to obtain a second cooperative score.

Further, before obtaining a plurality of primary products of a primary matching enterprise and a secondary matching enterprise, the method further comprises obtaining a concern between the primary matching enterprise and the secondary matching enterprise;

calculating attention condition scores of the primary matching enterprises and the secondary matching enterprises according to the attention conditions;

calculating a third score of the intention of collaboration according to the attention condition score and the first score of the intention of collaboration;

and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the third intention of cooperation score.

Further, the attention condition comprises mutual attention between the primary matching enterprise and the secondary matching enterprise, and one-way attention between the primary matching enterprise and the secondary matching enterprise;

calculating the interest profile scores for the primary and secondary matching businesses based on the interest profile further comprises,

and taking the score corresponding to the mutual attention between the primary matching enterprise and the secondary matching enterprise or the score corresponding to the one-way attention between the matching enterprise and the secondary matching enterprise as the attention situation score.

Further, calculating an intent-to-collaborate third score based on the attention situation score and the intent-to-collaborate first score further comprises,

and according to a preset weight, calculating the sum of the attention condition score and the first score of the cooperative interest to obtain a third score of the cooperative interest.

Further, before obtaining a plurality of primary products of the primary matching enterprise and the secondary matching enterprise, the method further comprises,

acquiring a matching enterprise range of the primary matching enterprise, and calculating enterprise range scores of the primary matching enterprise and the secondary matching enterprise according to the matching enterprise range and the secondary matching enterprise;

obtaining the attention condition between the primary matching enterprise and the secondary matching enterprise, and calculating the attention condition scores of the primary matching enterprise and the secondary matching enterprise according to the attention condition;

calculating an intention of collaboration fourth score according to the enterprise-wide score, the attention situation score and the intention of collaboration first score;

and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the fourth score of the intention of cooperation.

Further, calculating an intent-to-collaborate fourth score based on the business segment score, the concern score, and the intent-to-collaborate first score further comprises,

and calculating the sum of the enterprise range score, the attention situation score and the first score of the cooperative intention according to a preset weight to obtain a fourth score of the cooperative intention.

Further, evaluating the intent-of-collaboration between the primary and secondary matching businesses based on the intent-of-collaboration first score further comprises,

determining an intention of collaboration level to which the intention of collaboration first score belongs, each level of the intention of collaboration level including an upper limit value of the intention of collaboration score and a lower limit value of the intention of collaboration first score;

and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the intention of cooperation level.

On the other hand, the embodiment of the invention also provides a device for quantitatively evaluating the inter-enterprise cooperation intention, which comprises:

the system comprises a primary operation product acquisition unit, a secondary matching enterprise acquisition unit and a matching enterprise management unit, wherein the primary operation product acquisition unit is used for acquiring a plurality of primary operation products of a primary matching enterprise and a secondary matching enterprise, and the requirement types of the primary operation products of the primary matching enterprise and the requirement types of the primary operation products of the secondary matching enterprise can achieve cooperation;

the matching degree score calculating unit is used for calculating matching degree scores between a plurality of main products of the secondary matching enterprises and main products of the main matching enterprises through a natural language recognition algorithm, and the numerical value of the matching degree score is between 0 and 1;

the intention-of-collaboration score calculating unit is used for sorting the matching degree scores corresponding to a plurality of main products of the secondary matching enterprise in a descending order; according to the formula:

and the intention evaluation unit is used for evaluating the intention of cooperation between the primary matching enterprises and the secondary matching enterprises according to the intention score.

In another aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the above method when executing the computer program.

In another aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the above method.

Finally, an embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and the computer program is executed by a processor to implement the method.

In the embodiment of the invention, the matching degree score of each primary product of the secondary matching enterprise and the primary product of the primary matching enterprise is respectively calculated through a natural language identification algorithm to obtain a plurality of matching degree scores with the numerical value between 0 and 1, the higher the matching degree score is, the higher the possibility that cooperation can be formed between the primary product of the secondary matching enterprise and the primary product of the primary matching enterprise is, then the matching degree scores are sorted in a descending order, the first score of the cooperation intention is calculated according to each matching degree score sorted in the descending order, finally the cooperation intention between the primary matching enterprise and the secondary matching enterprise can be evaluated according to the first score of the cooperation intention, the calculation of the cooperation intention score of the primary matching enterprise and the secondary matching enterprise according to the primary product of the primary matching enterprise and the primary product of the secondary matching enterprise is realized, the cooperation intention of the primary matching enterprise and the secondary matching enterprise can be quantitatively evaluated, plays a certain guiding role in the cooperative negotiation between the main matching enterprise and the secondary matching enterprise. Compared with the scheme of analyzing the cooperation possibility between the cooperation-treating enterprise and the target cooperation enterprise by using the manual experience in the prior art, the method solves the problems that the workload for analyzing the cooperation possibility between the cooperation-treating enterprise and the target cooperation enterprise by using the manual experience is large, the efficiency is low, and the manual experience cannot quantitatively analyze the cooperation possibility between the enterprises, so that certain errors exist in an analysis result.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:

FIG. 1 is a schematic diagram of a system for quantitatively evaluating inter-enterprise intentions of collaboration according to an embodiment of the present invention;

FIG. 2 is a flowchart illustrating a method for quantitative evaluation of inter-enterprise willingness to collaborate according to an embodiment of the present invention;

FIG. 3 is a process for calculating a match score according to an embodiment of the present invention;

FIG. 4 is a process for evaluating the intent-to-collaborate based on matching business segment and degree of match between hosted products, in accordance with an embodiment of the present invention;

FIG. 5 is a process for evaluating the intention of collaboration based on the inter-enterprise concerns and the matching between the primary products, according to an embodiment of the present invention.

FIG. 6 is a process for evaluating the intention of collaboration based on matching business scope, inter-business concerns, and matching between hosted products, in accordance with an embodiment of the present invention.

FIG. 7 is a schematic structural diagram illustrating an apparatus for quantitatively evaluating inter-enterprise intentions of collaboration according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present invention.

Description of the symbols of the drawings:

101. a terminal;

102. a server;

701. a main operation product acquisition unit;

702. a matching degree score calculation unit;

703. an intention-of-collaboration score calculation unit;

704. an intention-of-collaboration evaluation unit;

802. a computer device;

804. a processing device;

806. a storage resource;

808. a drive mechanism;

810. an input/output module;

812. an input device;

814. an output device;

816. a presentation device;

818. a graphical user interface;

820. a network interface;

822. a communication link;

824. a communication bus.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or device.

It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.

Fig. 1 is a schematic diagram of an implementation system of a quantitative evaluation method of inter-enterprise cooperation intention according to an embodiment of the present invention, and the implementation system may include a terminal 101 and a server 102, where the terminal 101 and the server 102 establish a communication connection to enable data interaction. The terminal 101 may input a primary operation product of a primary matching enterprise and a plurality of primary operation products of a secondary matching enterprise to the server 102, where a requirement type of the primary operation product of the primary matching enterprise and a requirement type of the plurality of primary operation products of the secondary matching enterprise may achieve cooperation, the server 102 calculates an intention of cooperation score of the primary matching enterprise and the secondary matching enterprise according to the primary operation product of the primary matching enterprise and the plurality of primary operation products of the secondary matching enterprise, quantitatively evaluates an intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the intention of cooperation score, and sends an evaluation result to the terminal 101, so that the terminal 101 displays the intention of cooperation between the primary matching enterprise and the secondary matching enterprise to the primary matching enterprise or the secondary matching enterprise, and plays a certain guiding role in cooperation negotiation between the primary matching enterprise and the secondary matching enterprise.

In this embodiment, the server 102 may be an independent physical server, may also be a server cluster or a distributed system formed by a plurality of physical servers, and may also be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), and a big data and artificial intelligence platform.

In an alternative embodiment, the terminal 101 may evaluate the intention of collaboration between the primary matching enterprise and the secondary matching enterprise in conjunction with the server 102. In particular, the terminal 101 may include, but is not limited to, a smart phone, a desktop computer, a tablet computer, a laptop computer, a smart speaker, a digital assistant, an Augmented Reality (AR)/Virtual Reality (VR) device, a smart wearable device, and other types of electronic devices. Optionally, the operating system running on the electronic device may include, but is not limited to, an android system, an IOS system, Linux, Windows, and the like.

In addition, it should be noted that fig. 1 shows only one application environment provided by the present disclosure, and in practical applications, other application environments may also be included, and this specification is not limited.

Specifically, the implementation of the invention provides a quantitative evaluation method for inter-enterprise cooperation intention, which can quantitatively evaluate the cooperation intention between a primary matching enterprise and a secondary matching enterprise. Fig. 2 is a flowchart illustrating a quantitative evaluation method of inter-enterprise collaboration intention according to an embodiment of the present invention, in which a process of quantitatively evaluating collaboration intention between a primary matching enterprise and a secondary matching enterprise according to a primary product of the primary matching enterprise and a plurality of primary products of the secondary matching enterprise is described, but more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual system or apparatus product executes, it can execute sequentially or in parallel according to the method shown in the embodiment or the figures. Specifically, as shown in fig. 2, the method may include:

step 201: acquiring a plurality of primary operation products of a primary matching enterprise and a secondary matching enterprise, wherein the demand type of the primary operation products of the primary matching enterprise and the demand type of the plurality of primary operation products of the secondary matching enterprise can achieve cooperation;

step 202: calculating matching degree scores between a plurality of main products of the secondary matching enterprises and main products of the main matching enterprises through a natural language recognition algorithm, wherein the numerical value of the matching degree score is between 0 and 1;

step 203: sorting the matching degree scores corresponding to a plurality of main marketing products of the secondary matching enterprise in a descending order;

step 204: calculating an intention-of-collaboration first score according to formula (1) of the specification;

in this step, formula (1) is:

wherein S represents the first score of the intention of collaboration, S ₁ Representing the matchability score first in the descending ordering, S ₂ Representing the degree of match score, S, ranked second in the descending order ₃ Representing the degree of match score, S, ranked second in the descending order _n-2 Representing the matchedness score of the n-2 th rank in the descending ordering, S _n-1 Representing the matchedness score, S, of the n-1 th rank in the descending order _n Representing the matchability score for the nth rank in the descending order;

step 205: and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the intention of cooperation first score.

By the method of the embodiment of the invention, the matching degree score of each primary product of the secondary matching enterprise and the primary product of the primary matching enterprise is respectively calculated by a natural language identification algorithm to obtain a plurality of matching degree scores with the numerical values between 0 and 1, the higher the matching degree score is, the higher the possibility that cooperation can be formed between the primary product of the secondary matching enterprise and the primary product of the primary matching enterprise is, then the matching degree scores are sorted in a descending order, the first score of the cooperation intention is calculated according to each matching degree score sorted in the descending order, finally the cooperation intention between the primary matching enterprise and the secondary matching enterprise can be evaluated according to the first score of the cooperation intention, the calculation of the cooperation intention of the primary matching enterprise and the secondary matching enterprise according to the primary product of the primary matching enterprise and the primary product of the secondary matching enterprise is realized, the cooperation intention of the primary matching enterprise and the secondary matching enterprise can be quantitatively evaluated, plays a certain guiding role in the cooperative negotiation between the main matching enterprise and the secondary matching enterprise. Compared with the scheme of analyzing the cooperation possibility between the cooperation-treating enterprise and the target cooperation enterprise by using the manual experience in the prior art, the method solves the problems that the workload for analyzing the cooperation possibility between the cooperation-treating enterprise and the target cooperation enterprise by using the manual experience is large, the efficiency is low, and the manual experience cannot quantitatively analyze the cooperation possibility between the enterprises, so that certain errors exist in an analysis result.

In the embodiment of the present invention, the requirement type may include purchase and sale, and the requirement type of the primary product of the primary matching enterprise and the requirement types of the plurality of primary products of the secondary matching enterprise can achieve cooperation, for example, if the requirement type of the primary product a of the primary matching enterprise is purchase and the requirement types of the plurality of primary products B, C, D of the secondary matching enterprise are sale, the primary product a of the primary matching enterprise and the primary product B, C, D of the secondary matching enterprise can achieve cooperation. And then, calculating matching degree scores between the major product B, C, D of the secondary matching enterprise and the major product A of the major matching enterprise respectively through a natural language recognition algorithm, specifically, calculating the similarity of the major product B and the major product A, the major product C and the major product A, and the major product D and the major product A on the text through an autodialect recognition algorithm, wherein the higher the similarity is, the higher the matching degree score is. The numerical size of the matching degree score is between 0 and 1.

For example, the matching degree score of the primary product B and the primary product a is 0.8, the matching degree score of the primary product C and the primary product a is 0.7, the matching degree score of the primary product D and the primary product a is 0.6, the descending order is 0.8, 0.7 and 0.6, and then the first score of the collaboration intention is 1.376 according to the formula (1).

And evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the first intention of cooperation first score, wherein the higher the first intention of cooperation is, the stronger the intention of cooperation between the primary matching enterprise and the secondary matching enterprise is.

It should be noted that, when one primary matching enterprise and a plurality of secondary matching enterprises perform quantitative evaluation of the collaboration intention, the primary products of the plurality of secondary matching enterprises should be the same in quantity. And evaluating the collaboration intention between the multiple secondary matching enterprises and the same primary matching enterprise according to the collaboration intention first score, so that the primary matching enterprise can select a final collaboration enterprise from the multiple secondary matching enterprises according to the collaboration intention score. When there are a plurality of primary products of the primary matching enterprise, the first score of the corresponding collaboration intention of each primary product of the primary matching enterprise needs to be calculated according to the steps 202 to 204, and then the average value is obtained to obtain the final first score of the collaboration intention of the primary matching enterprise and the secondary matching enterprise.

According to an embodiment of the present invention, the step 202 of calculating a matching degree score between the plurality of primary products of the secondary matching business and the primary products of the primary matching business through a natural language recognition algorithm further comprises,

In the embodiment of the present invention, the first matching word set may be an identical word set of a main product of the main matching enterprise, and the second matching word set may be a synonym set of a main product of the main matching enterprise. It can be understood that the words in the same word set are the same as the main products of the main matching enterprise, and the words in the synonym set are semantically the same as the main products of the main matching enterprise. And then carrying out similarity matching on the primary operation product of the secondary matching enterprise and the same word set or synonym set of the primary operation product of the primary matching enterprise, and calculating the matching degree score between the primary operation product of the secondary matching enterprise and the primary operation product of the primary matching enterprise according to the similarity matching result. Optionally, since the words in the same word set are the same as the primary products of the primary matching enterprise, the matching degree between the primary products of the secondary matching enterprise and the same word set can be given a higher weight, and the words in the synonym set are semantically the same as the primary products of the primary matching enterprise, so that the matching degree between the primary products of the secondary matching enterprise and the same word set can be given a lower weight, and the sum of the two matching degrees is calculated according to the weights and serves as the matching degree score between one primary product of the secondary matching enterprise and the primary products of the primary matching enterprise.

Preferably, in order to improve the calculation efficiency, according to an embodiment of the present invention, as shown in fig. 3, the process of performing similarity matching on the primary product of the secondary matching enterprise and the first matchword set or the second matchword set of the primary product of the primary matching enterprise, and calculating the matching score between the primary product of the secondary matching enterprise and the primary product of the primary matching enterprise according to the similarity matching result further includes,

step 301: performing first similarity matching on a primary operation product of the secondary matching enterprise and a first matching word set of the primary operation product of the primary matching enterprise;

step 302: if the first similarity matching is successful, the matching degree score is a first preset value;

step 303: if the first similarity matching is not successful, performing second similarity matching on the primary operation product of the secondary matching enterprise and a second matching word set of the primary operation product of the primary matching enterprise;

step 304: and if the second similarity matching is successful, the matching score is a second preset value.

It can be understood that the primary operation product of the secondary matching enterprise is firstly matched with the same word set, if the matching is successful, the primary operation product of the secondary matching enterprise is completely the same as the primary operation product of the primary matching enterprise, and the primary operation product is not matched with the synonym set.

It should be noted that the first preset value and the second preset value may be set according to service requirements, and the first preset value should be greater than the second preset value.

In order to further extend the matching range, if the second similarity matching in step 303 is not successful, according to an embodiment of the present invention, the method further includes,

In the embodiment of the present invention, the third matching word set, the fourth matching word set, and the fifth matching word set may respectively represent a similar word set, an upper-level word set, and a lower-level word set, and it may be understood that words in the similar word set are semantically similar to a main-line product of a main matching enterprise, words in the upper-level word set are semantically upper-level words of the main-line product of the main matching enterprise, and words in the lower-level word set are semantically lower-level words of the main-line product of the main matching enterprise. And then respectively carrying out third similarity matching, fourth similarity matching and fifth similarity matching on the primary operation products of the secondary matching enterprises and the similarity word set, the superior word set and the inferior word set of the primary matching enterprise to respectively obtain matching degree scores corresponding to the third similarity matching, the fourth similarity matching and the fifth similarity matching, wherein the matching degree score corresponding to the third similarity matching is a third preset value, the matching degree score corresponding to the fourth similarity matching is a fourth preset value, and the matching degree score corresponding to the fifth similarity matching is a fifth preset value. It should be noted that, because the words of the similar word set, the hypernym set, or the hyponym set are not completely the same as the main products of the main matching enterprise, it is necessary to match one main product of the secondary matching enterprise with the words of the similar word set, the hypernym set, or the hyponym set, respectively, to obtain three different matching degrees, and then the largest value of the three matching degrees is taken as the matching degree score between one main product of the secondary matching enterprise and one main product of the main matching enterprise.

According to an embodiment of the present invention, in order to further improve the accuracy of evaluating the collaboration intention of the primary matching enterprise and the secondary matching enterprise, more evaluation factors may be added, such as a matching range predetermined by the primary matching enterprise, attention between the primary matching enterprise and the secondary matching enterprise, and the like, and the collaboration intention between the primary matching enterprise and the secondary matching enterprise is evaluated by combining the method shown in fig. 2 of this specification.

Specifically, according to an embodiment of the present invention, as shown in fig. 4, before the step 201 obtains a plurality of primary products of the primary matching enterprise and the secondary matching enterprise, the method further includes,

step 401: acquiring a matching enterprise range of the main matching enterprise;

step 402: calculating enterprise range scores of the primary matching enterprise and the secondary matching enterprises according to the matching enterprise ranges and the secondary matching enterprises;

step 403: calculating an intention of collaboration second score based on the business range score and the intention of collaboration first score;

step 404: and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the second intention of cooperation score.

In the embodiment of the present invention, the matching enterprise scope of the master matching enterprise includes a plurality of enterprises, and the matching enterprise scope of the master matching enterprise may be preset by a worker of the master matching enterprise, for example, the worker of the master matching enterprise screens out an enterprise meeting the requirement of the worker from a large number of enterprises in advance through market research and other manners, so as to obtain the matching enterprise scope of the master matching enterprise. Then, enterprise range scores of the primary matching enterprise and the secondary matching enterprise are calculated according to the matching enterprise range and the secondary matching enterprise, for example, a worker of the primary matching enterprise sets scores for a plurality of enterprises in the matching enterprise range in advance, secondary matching enterprises are searched in a matching enterprise list, if the secondary matching enterprises are found, the found scores of the enterprises are used as enterprise range scores of the secondary matching enterprises, then, a second cooperation intention score is calculated according to the enterprise range scores and the first cooperation intention score obtained in step 204, and optionally, the sum of the enterprise range scores and the first cooperation intention score can be calculated and used as the second cooperation intention score. And finally evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the second intention of cooperation score. It is understood that the higher the second score of the interest of collaboration, the stronger the interest of collaboration between the primary and secondary matching enterprises.

According to one embodiment of the present invention, calculating 402 a business-wide score for the primary and secondary matching businesses based on the matching business range and the secondary matching business further comprises,

In the embodiment of the present invention, the staff of the master matching enterprise may classify a plurality of enterprises in the matching enterprise scope into different scoring levels, that is, the matching enterprise scope includes enterprises corresponding to a plurality of levels, and an enterprise at each level corresponds to the target matching enterprise scope. Firstly, determining a target matching enterprise range to which the secondary matching enterprise belongs in the matching enterprise range, namely determining the grade corresponding to the secondary matching enterprise, and then taking the score corresponding to the determined grade as the enterprise matching range score.

In the embodiment of the present invention, since the matching enterprise range of the primary matching enterprise is determined by the staff of the primary matching enterprise performing market research in advance and the like, and there is a certain subjective factor, in order to improve the accuracy of quantitatively evaluating the collaboration intention between the primary matching enterprise and the secondary matching enterprise, it is necessary to comprehensively consider the enterprise-range score and the collaboration intention first score calculated according to the matching degree of the primary products of the enterprise. Thus, according to one embodiment of the invention, calculating 403 an intent-of-collaboration second score based on the business-wide score and the intent-of-collaboration first score further comprises,

In the embodiment of the invention, model analysis can be performed on historical collaboration conditions of a plurality of enterprises and main business products and matching enterprise ranges of the plurality of enterprises to obtain an optimal weight value as the predetermined weight, and then the sum of the enterprise range score and the first score of the intention of collaboration is calculated according to the predetermined weight to obtain the second score of the intention of collaboration. It can be understood that the second score of the intention of collaboration comprehensively considers the enterprise range score obtained according to the matching enterprise range preset by the staff of the primary matching enterprise and the first score of the enterprise matching range calculated according to the primary products of the primary matching enterprise and the primary products of the secondary matching enterprise to obtain the optimal second score of the intention of collaboration capable of representing the intention of collaboration between the primary matching enterprise and the secondary matching enterprise, thereby improving the accuracy of quantitatively evaluating the intention of collaboration between the primary matching enterprise and the secondary matching enterprise.

In accordance with one embodiment of the present invention, as shown in fig. 5, before obtaining a plurality of primary products of the primary matching enterprise and the secondary matching enterprise in step 201, the method further comprises,

step 501: acquiring the attention condition between the primary matching enterprise and the secondary matching enterprise;

step 502: calculating attention condition scores of the primary matching enterprises and the secondary matching enterprises according to the attention conditions;

step 503: calculating a third score of the intention of collaboration according to the attention condition score and the first score of the intention of collaboration;

step 504: and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the third intention of cooperation score.

In the embodiment of the invention, the staff of the primary matching enterprise or the secondary matching enterprise can pay attention to one or more enterprises in advance in a market investigation mode and other modes, such as paying attention to the WeChat public numbers, microblogs and the like of the enterprises. For example, if the staff of the primary matching enterprise pays attention to the enterprise a in advance, it indicates that the possibility that the enterprise a can achieve collaboration with the primary matching enterprise is high, and therefore, the attention situation scores of the primary matching enterprise and the secondary matching enterprise are calculated according to the attention situation, and then the third cooperative intention score is calculated according to the attention situation score and the first cooperative intention score obtained in step 204; to evaluate the intent of collaboration between the primary and secondary matching businesses based on the intent of collaboration third score. If the third score is higher, the stronger the intention of cooperation between the main matching enterprise and the secondary matching enterprise is.

According to an embodiment of the present invention, the concern condition in step 501 includes mutual concern between the primary matching enterprise and the secondary matching enterprise, and unidirectional concern between the primary matching enterprise and the secondary matching enterprise. It can be understood that when the primary matching enterprise and the secondary matching enterprise concern each other, the primary matching enterprise and the secondary matching enterprise are both interested in the opposite party, which indicates that the cooperation possibility between the primary matching enterprise and the secondary matching enterprise is strong; when one-way attention is paid between the primary matching enterprise and the secondary matching enterprise, one party is interested in the other party in a unilateral way, and certain cooperation possibility also exists between the primary matching enterprise and the secondary matching enterprise. Calculating an attention score for the primary and secondary matching businesses based on the attention further comprises,

In the embodiment of the present invention, the score corresponding to the mutual attention or the score corresponding to the one-way attention may be set according to the needs of the primary matching enterprise or the secondary matching enterprise, and it should be noted that the score corresponding to the mutual attention should be higher than the score corresponding to the one-way attention.

According to one embodiment of the invention, the step 503 of calculating an intentional third score based on the situational interest score and the intentional first score further comprises,

In the embodiment of the invention, model analysis can be performed on historical collaboration situations of a plurality of enterprises and main products and attention situations of the plurality of enterprises to obtain an optimal weight value as the predetermined weight, and then the sum of the attention situation score and the first cooperation intention score is calculated according to the predetermined weight to obtain the third cooperation intention score. It can be understood that the third score of the intention of collaboration comprehensively considers the attention situation score obtained from the attention situation of the primary matching enterprise or the secondary matching enterprise to obtain the optimal third score of the intention of collaboration capable of representing the intention of collaboration between the primary matching enterprise and the secondary matching enterprise according to the first score of the enterprise matching range calculated from the primary products of the primary matching enterprise and the primary products of the secondary matching enterprise, thereby improving the accuracy of quantitatively evaluating the intention of collaboration between the primary matching enterprise and the secondary matching enterprise.

In some other embodiments of the present invention, the enterprise matching range, the concern, and the matching degree between the enterprise primary products may also be combined at the same time, specifically, as shown in fig. 6, before the step 201 obtains a plurality of primary products of the primary matching enterprise and the secondary matching enterprise, the method further includes,

step 601: acquiring a matching enterprise range of the primary matching enterprise, and calculating enterprise range scores of the primary matching enterprise and the secondary matching enterprise according to the matching enterprise range and the secondary matching enterprise;

step 602: obtaining the attention condition between the primary matching enterprise and the secondary matching enterprise, and calculating the attention condition scores of the primary matching enterprise and the secondary matching enterprise according to the attention condition;

step 603: calculating an intention of collaboration fourth score according to the enterprise-wide score, the attention situation score and the intention of collaboration first score;

step 604: and evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the fourth score of the intention of cooperation.

Further, the step 603 of calculating an intent-to-collaborate fourth score based on the business-wide score, the interest-status score, and the intent-to-collaborate first score further comprises,

In the embodiment of the present invention, model analysis may be performed on historical collaboration situations of a plurality of enterprises and main products, matching enterprise scopes, and attention situations of the plurality of enterprises to obtain an optimal weight value as the predetermined weight, and then a fourth score of the intention of collaboration is obtained by calculating a sum of an enterprise scope score, an attention situation score, and the first score of the intention of collaboration according to the predetermined weight.

According to one embodiment of the present invention, the step 205 of evaluating the intent of collaboration between the primary and secondary matching businesses based on the intent of collaboration first score further comprises,

In the embodiment of the present invention, model analysis may be performed on historical collaboration situations (for example, collaboration negotiation, collaboration offers, contract-signing collaboration, etc.) of multiple enterprises and first scores of collaboration intentions of each enterprise, and the historical first scores of multiple collaboration intentions are divided into multiple levels of collaboration intentions, which correspond to multiple historical collaboration situations. And finally evaluating the intention of cooperation between the primary matching enterprise and the secondary matching enterprise according to the intention level of cooperation.

The embodiment of the invention also provides a device for quantitatively evaluating the inter-enterprise cooperation intention, as shown in fig. 7, which comprises,

a primary operation product obtaining unit 701, configured to obtain multiple primary operation products of a primary matching enterprise and a secondary matching enterprise, where a requirement type of the primary operation product of the primary matching enterprise and a requirement type of the multiple primary operation products of the secondary matching enterprise can achieve cooperation;

a matching degree score calculating unit 702, configured to calculate, through a natural language identification algorithm, matching degree scores between a plurality of primary products of the secondary matching enterprise and primary products of the primary matching enterprise, where a numerical value of the matching degree score is between 0 and 1;

an intention-of-collaboration score calculation unit 703, configured to sort the matching degree scores corresponding to the multiple primary products of the secondary matching enterprise in a descending order; according to the formula:

and an intention of collaboration evaluation unit 704 for evaluating an intention of collaboration between the primary matching business and the secondary matching business based on the intention of collaboration score.

Because the principle of the device for solving the problems is similar to that of the method, the implementation of the device can be referred to the implementation of the method, and repeated details are not repeated.

Fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present invention, where an apparatus in the present invention may be the computer device in the embodiment, and execute the method of the present invention. Computer device 802 may include one or more processing devices 804, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The computer device 802 may also include any storage resources 806 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, storage resources 806 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage resource may use any technology to store information. Further, any storage resource may provide volatile or non-volatile reservation of information. Further, any storage resources may represent fixed or removable components of computer device 802. In one case, when the processing device 804 executes associated instructions stored in any storage resource or combination of storage resources, the computer device 802 can perform any of the operations of the associated instructions. The computer device 802 also includes one or more drive mechanisms 808, such as a hard disk drive mechanism, an optical disk drive mechanism, etc., for interacting with any storage resource.

Computer device 802 may also include an input/output module 810(I/O) for receiving various inputs (via input device 812) and for providing various outputs (via output device 814). One particular output mechanism may include a presentation device 816 and an associated Graphical User Interface (GUI) 818. In other embodiments, input/output module 810(I/O), input device 812, and output device 814 may also be excluded, as just one computer device in a network. Computer device 802 may also include one or more network interfaces 820 for exchanging data with other devices via one or more communication links 822. One or more communication buses 824 couple the above-described components together.

Communication link 822 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 822 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements the above method.

An embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements the method described above.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. A quantitative evaluation method of inter-enterprise cooperation intention is characterized by comprising the following steps,

according to the formula:

2. The method of claim 1, wherein calculating a matching score between the plurality of primary products of the secondary matching business and the primary products of the primary matching business via a natural language identification algorithm further comprises,

analyzing the main business products of the main matching enterprise through a natural language recognition algorithm to obtain a first matching word set and a second matching word set of the main business products of the main matching enterprise;

3. The method of claim 2, wherein the inter-enterprise collaboration intent is evaluated,

performing similarity matching on the primary operation product of the secondary matching enterprise and the first matching word set or the second matching word set of the primary operation product of the primary matching enterprise, and calculating a matching degree score between the primary operation product of the secondary matching enterprise and the primary operation product of the primary matching enterprise according to a similarity matching result further comprises,

4. The method of claim 3, wherein if the second similarity match is not successful, the method further comprises,

5. The method of claim 1, wherein prior to obtaining a plurality of primary products of a primary matching business and a secondary matching business, the method further comprises,

acquiring a matching enterprise range of the main matching enterprise;

6. The method of claim 5, wherein calculating enterprise-wide scores for the primary and secondary matching enterprises based on the matching enterprise-wide and secondary matching enterprises further comprises,

7. The method of claim 5, wherein calculating an intent-to-collaborate second score based on the business-wide score and the intent-to-collaborate first score further comprises,

8. The method of claim 1, wherein prior to obtaining a plurality of primary products of a primary matching business and a secondary matching business, the method further comprises,

acquiring the attention condition between the primary matching enterprise and the secondary matching enterprise;

9. The method according to claim 8, wherein the concern situation includes mutual concern between the primary matching enterprise and the secondary matching enterprise, and one-way concern between the primary matching enterprise and the secondary matching enterprise;

10. The method of claim 8, wherein calculating a third score for interest based on the interest-bearing score and the first score for interest further comprises,

11. The method of claim 1, wherein prior to obtaining a plurality of primary products of a primary matching business and a secondary matching business, the method further comprises,

12. The method of claim 11, wherein calculating a fourth score for interest of collaboration based on the business segment score, the concern score, and the first score for interest of collaboration further comprises,

13. The method of claim 1, wherein evaluating the intent of collaboration between the primary and secondary matching businesses based on the intent of collaboration first score further comprises,

14. An apparatus for quantitatively evaluating inter-enterprise cooperation intention, comprising:

the system comprises a main operation product acquisition unit, a main operation product acquisition unit and a secondary matching enterprise management unit, wherein the main operation product acquisition unit is used for acquiring a plurality of main operation products of a main matching enterprise and a secondary matching enterprise, and the requirement types of the main operation products of the main matching enterprise and the requirement types of the plurality of main operation products of the secondary matching enterprise can achieve cooperation;

15. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 13 when executing the computer program.

16. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 13.

17. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 13.