Enterprise recommendation method and device of industrial chain, equipment and storage medium

Abstract

The invention relates to the technical field of information and recommendation, and discloses an enterprise recommendation method, device and equipment of an industry chain and a storage medium, and the method comprises the steps: obtaining a tax payment credit rating and the number of bad judicial records in credit information, obtaining a score corresponding to the tax payment credit rating, obtaining a score corresponding to the number of bad judicial records, and obtaining a score corresponding to the number of bad judicial records; obtaining the total number of employees in the contribution information, and obtaining a score corresponding to the total number of employees; adding the score corresponding to the industrial integrating degree, the score corresponding to the node position, the patent score, the copyright score, the score corresponding to the enterprise label, the score corresponding to the tax payment credit rating, the score corresponding to the number of bad judicial records and the score corresponding to the total number of employees to generate a total score corresponding to the current enterprise, and according to a sequence from large to small, calculating the total score of the current enterprise. And sorting the total score corresponding to each current enterprise, and recommending the current enterprises which are sorted in the first N positions as target enterprises of the industry chain. The recommendation efficiency of the target enterprise can be improved.

Description

Technical Field

[0001] The present invention relates to the fields of information technology and recommendation technology, and in particular to an enterprise recommendation method, device, equipment and storage medium for an industrial chain. Background Art

[0002] The entry of target enterprises in the industrial chain can improve the industrial chain structure of the industrial park, promote close cooperation and resource sharing between upstream and downstream enterprises, form an industrial agglomeration effect, and enhance the industrial competitiveness and comprehensive benefits of the entire industrial park. Therefore, introducing target enterprises in the industrial chain is a key strategy to enhance the comprehensive competitiveness of the industrial park.

[0003] However, the recommendation process of the target enterprises in the existing industrial chain is cumbersome, which is not conducive to improving the recommendation efficiency of the target enterprises. The reason is that the existing technology mainly adopts the manual recommendation method to recommend the target enterprises in the industrial chain, and the manual recommendation method consumes a lot of human resources and time resources, increases the recommendation time of the target enterprises in the industrial chain, and is easily affected by manual intervention, so it is not conducive to improving the recommendation efficiency of the target enterprises. Summary of the invention

[0004] The present invention provides an enterprise recommendation method, device, computer equipment and storage medium for an industrial chain, so as to solve the technical problem that the recommendation process of target enterprises in the existing industrial chain is cumbersome and is not conducive to improving the recommendation efficiency of target enterprises.

[0005] In the first aspect, a method for recommending enterprises in an industrial chain is provided, including: Obtain the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information; Obtaining the industry fit degree and the position of the current enterprise in the industry chain in the industry information, selecting the position of the current enterprise in the industry chain as the node position, and obtaining the score corresponding to the industry fit degree and the score corresponding to the node position; The scores corresponding to the industry fit and the node position are stored, and the patent score and copyright score are obtained based on the innovation information; The patent score and the copyright score are stored, the number of branches and the number of abnormal operations in the business information are obtained, the score corresponding to the number of branches is obtained, and the score corresponding to the number of abnormal operations is obtained; The scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations are stored, the enterprise label in the growth information is obtained, the score corresponding to the enterprise label is obtained, the tax credit rating and the number of bad judicial records in the credit information are obtained, the score corresponding to the tax credit rating is obtained, the score corresponding to the number of bad judicial records is obtained, the total number of employees in the contribution information is obtained, and the score corresponding to the total number of employees is obtained; The scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate the total score corresponding to the current enterprise. The total scores corresponding to each current enterprise are sorted in descending order, and the current enterprises in the top N positions are recommended as the target enterprises of the industrial chain.

[0006] Further, the obtaining of the industry fit degree in the industry information and the position of the current enterprise in the industry chain, selecting the position of the current enterprise in the industry chain as the node position, and obtaining the score corresponding to the industry fit degree and the score corresponding to the node position include: Analyze the industrial information, and obtain the industrial fit and the position of the current enterprise in the industrial chain from the analyzed industrial information; Select the current enterprise's position in the industrial chain as the node position, obtain the score corresponding to the industry fit, and obtain the score corresponding to the node position.

[0007] Furthermore, the scores corresponding to the industry fit and the scores corresponding to the node positions are stored, and the patent scores and copyright scores are obtained based on the innovation information, including: Reading the first storage instruction, executing the first storage instruction, storing the score corresponding to the industry fit and the score corresponding to the node position, and obtaining a first storage result; When the status identifier in the first storage result is a success identifier, the total number of patents and the total number of software copyrights in the innovation information are obtained; the number of patents owned by every 100 people is obtained according to the total number of patents, the number of insured persons and the first model, and the score corresponding to the number of patents owned by every 100 people is obtained according to the corresponding relationship between the number of patents owned by every 100 people and the score, and the score corresponding to the number of patents owned by every 100 people is selected as the patent score; the number of software copyrights owned by every 100 people is obtained according to the total number of patents, the number of insured persons and the second model, and the score corresponding to the number of software copyrights owned by every 100 people is obtained according to the corresponding relationship between the number of software copyrights owned by every 100 people and the score, and the score corresponding to the number of software copyrights owned by every 100 people is selected as the copyright score; wherein, the first model is: the number of patents owned by every 100 people = (total number of patents ÷ number of insured persons) × 100; wherein, the second model is: the number of software copyrights owned by every 100 people = (total number of software copyrights ÷ number of insured persons) × 100.

[0008] Furthermore, the storing of the patent score and the copyright score, obtaining the number of branches and the number of abnormal operations in the business information, obtaining the score corresponding to the number of branches, and obtaining the score corresponding to the number of abnormal operations include: Read the second storage instruction, execute the second storage instruction, store the patent score and the copyright score, and obtain a second storage result; When the status identifier in the second storage result is a success identifier, the number of branches and the number of operating abnormalities in the operating information are obtained, and the score corresponding to the number of branches is obtained according to the first score table, and the score corresponding to the number of operating abnormalities is obtained according to the second score table.

[0009] Further, the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations are stored, the enterprise tags in the growth information are obtained, the scores corresponding to the enterprise tags are obtained, the tax credit rating and the number of bad judicial records in the credit information are obtained, the scores corresponding to the tax credit rating are obtained, the scores corresponding to the number of bad judicial records are obtained, the total number of employees in the contribution information are obtained, and the scores corresponding to the total number of employees are obtained, including: Reading the third storage instruction, executing the third storage instruction, storing the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, and obtaining a third storage result; When the status identifier in the third storage result is a success identifier, obtain the enterprise label in the growth information, obtain the score corresponding to the enterprise label according to the third score table, obtain the score corresponding to the tax credit rating according to the fourth score table, obtain the score corresponding to the number of bad judicial records according to the fifth score table, obtain the total number of employees in the contribution information, and obtain the score corresponding to the total number of employees according to the sixth score table.

[0010] Furthermore, the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate a total score corresponding to the current enterprise, and the total scores corresponding to each current enterprise are sorted in descending order, and the current enterprises in the top N positions are recommended as target enterprises of the industrial chain, including: Through the preset total score generation model, the scores corresponding to the industry fit, the scores corresponding to the node position, the patent score, the copyright score, the score corresponding to the enterprise label, the score corresponding to the tax credit rating, the score corresponding to the number of bad judicial records, and the score corresponding to the total number of employees are added together to generate the total score corresponding to the current enterprise; The sorting instruction in the register is read, and the total score corresponding to each current enterprise is sorted in descending order according to the sorting instruction, and the top 10 current enterprises are recommended as target enterprises of the industrial chain.

[0011] Furthermore, after the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate a total score corresponding to the current enterprise, the total scores corresponding to each current enterprise are sorted in descending order, and the current enterprises in the top N positions are recommended as target enterprises of the industrial chain, the enterprise recommendation method includes: The enterprise logo of the target enterprise is obtained, a prompt window is created, and the enterprise logo is displayed in the prompt window.

[0012] In a second aspect, a device for recommending enterprises in an industrial chain is provided, comprising: The first acquisition module is used to obtain the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information; The second acquisition module is used to obtain the industry fit degree and the position of the current enterprise in the industrial chain in the industrial information, select the position of the current enterprise in the industrial chain as the node position, and obtain the score corresponding to the industry fit degree and the score corresponding to the node position; The third acquisition module is used to store the scores corresponding to the industry fit and the scores corresponding to the node positions, and obtain the patent scores and copyright scores based on the innovation information; A fourth acquisition module is used to store the patent score and the copyright score, obtain the number of branches and the number of abnormal operations in the business information, obtain the score corresponding to the number of branches, and obtain the score corresponding to the number of abnormal operations; A fifth acquisition module is used to store the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, obtain the enterprise label in the growth information, obtain the score corresponding to the enterprise label, obtain the tax credit rating and the number of bad judicial records in the credit information, obtain the score corresponding to the tax credit rating, obtain the score corresponding to the number of bad judicial records, obtain the total number of employees in the contribution information, and obtain the score corresponding to the total number of employees; The recommendation module is used to add the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees to generate a total score corresponding to the current enterprise, sort the total scores corresponding to each current enterprise in order from large to small, and recommend the current enterprises in the top N positions as the target enterprises of the industrial chain.

[0013] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned enterprise recommendation method when executing the computer program.

[0014] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned enterprise recommendation method are implemented.

[0015] The present application provides a method, device, computer equipment and storage medium for recommending enterprises in an industrial chain. The beneficial effects are in two aspects. On the one hand, the current enterprises ranked in the top N are recommended as target enterprises in the industrial chain. Since no manual recommendation is required, the recommendation time of the target enterprises in the industrial chain is reduced, which is beneficial to improving the recommendation efficiency of the target enterprises in the industrial chain. On the other hand, since it will not be affected by manual intervention, it is beneficial to improve the reliability of the target enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0017] Figure 1 is a schematic diagram of an application environment of an enterprise recommendation method in one embodiment of the present invention; Figure 2 A schematic diagram of a process flow of an enterprise recommendation method provided by an embodiment of the present invention; Figure 3 yes Figure 2 A schematic flow chart of a specific implementation of step S23; Figure 4 yes Figure 2 A schematic flow chart of a specific implementation of step S25; Figure 5 yes Figure 2 A schematic flow chart of a specific implementation of step S26; Figure 6 is a structural schematic diagram of an enterprise recommendation device in one embodiment of the present invention; Figure 7 It is a structural diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 , Figure 1 is a schematic diagram of an application environment of an enterprise recommendation method according to an embodiment of the present invention. The enterprise recommendation method provided by the embodiment of the present invention can be applied in Figure 1 In an application environment, a client communicates with a server through a network.

[0020] The server obtains the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information through the client; Obtaining the industry fit degree and the position of the current enterprise in the industry chain in the industry information, selecting the position of the current enterprise in the industry chain as the node position, and obtaining the score corresponding to the industry fit degree and the score corresponding to the node position; The scores corresponding to the industry fit and the node position are stored, and the patent score and copyright score are obtained based on the innovation information; The patent score and the copyright score are stored, the number of branches and the number of abnormal operations in the business information are obtained, the score corresponding to the number of branches is obtained, and the score corresponding to the number of abnormal operations is obtained; The scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations are stored, the enterprise label in the growth information is obtained, the score corresponding to the enterprise label is obtained, the tax credit rating and the number of bad judicial records in the credit information are obtained, the score corresponding to the tax credit rating is obtained, the score corresponding to the number of bad judicial records is obtained, the total number of employees in the contribution information is obtained, and the score corresponding to the total number of employees is obtained; The scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate the total score corresponding to the current enterprise. The total scores corresponding to each current enterprise are sorted in descending order, and the current enterprises in the top N positions are recommended as the target enterprises of the industrial chain.

[0021] In the scheme implemented by the above-mentioned enterprise recommendation method, device, equipment and medium, the beneficial effects are in two aspects. On the one hand, the current enterprises ranked in the top N are recommended as the target enterprises of the industrial chain. Since no manual recommendation is required, the recommendation time of the target enterprises of the industrial chain is reduced, which is beneficial to improving the recommendation efficiency of the target enterprises of the industrial chain. On the other hand, since it will not be affected by manual intervention, it is beneficial to improve the reliability of the target enterprises.

[0022] The device running the client is referred to as a client device.

[0023] The device running the server is referred to as the server device.

[0024] Among them, client devices include but are not limited to smartphones, personal computers, Internet of Vehicles terminals, tablets and portable wearable devices.

[0025] The server device may be implemented by an independent server or a server cluster composed of multiple servers. The present invention is described in detail below through specific embodiments. Figure 2 , Figure 2 A flowchart of a method for recommending an enterprise according to an embodiment of the present invention includes the following steps: S21, obtain the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information; For example, the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information are obtained. Access a database and obtain the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information from the database.

[0026] S22, obtaining the industry fit degree in the industry information and the position of the current enterprise in the industry chain, selecting the position of the current enterprise in the industry chain as the node position, and obtaining the score corresponding to the industry fit degree and the score corresponding to the node position; The step of obtaining the industry fit degree and the position of the current enterprise in the industry chain in the industry information, selecting the position of the current enterprise in the industry chain as the node position, and obtaining the score corresponding to the industry fit degree and the score corresponding to the node position includes: Analyze the industrial information, and obtain the industrial fit and the position of the current enterprise in the industrial chain from the analyzed industrial information; Select the current enterprise's position in the industrial chain as the node position, obtain the score corresponding to the industry fit, and obtain the score corresponding to the node position.

[0027] Exemplarily, the position of the current enterprise in the industrial chain is selected as the node position, and the score corresponding to the industrial fit is obtained. The score corresponding to the node position is obtained, including: Select the current position of the enterprise in the industrial chain as the node position to obtain the current level of industrial fit; When the current level is the first level, the score of the first level is selected as the score corresponding to the industry fit; when the current level is the second level, the score of the second level is selected as the score corresponding to the industry fit; When the node position is the position of a level 1 node in the industrial chain, the score of the level 1 node is selected as the score corresponding to the node position; when the node position is the position of a level 2 node in the industrial chain, the score of the level 2 node is selected as the score corresponding to the node position; when the node position is the position of a level 3 node in the industrial chain, the score of the level 3 node is selected as the score corresponding to the node position; when the node position is the position of a level 4 node in the industrial chain, the score of the level 4 node is selected as the score corresponding to the node position; when the node position is the position of other nodes in the industrial chain, the scores of other nodes are selected as the scores corresponding to the node position.

[0028] Among them, industrial fit refers to the degree of mutual matching and coordination in resource utilization between different industries or between various links within an industry.

[0029] Among them, the first level is higher than the second level.

[0030] Optionally, the score of the first level is 8 points and the score of the second level is 5 points.

[0031] Among them, the node positions include the position of level 1 nodes in the industrial chain, the position of level 2 nodes in the industrial chain, the position of level 3 nodes in the industrial chain, the position of level 4 nodes in the industrial chain, and the positions of other nodes.

[0032] Among them, the score of level 1 node is 8 points; the score of level 2 node is 7 points.

[0033] Among them, the score of level 3 node: 6 points; the score of level 4 node: 5 points Among them, the score of other nodes: 4 points.

[0034] Among them, the position of level 1 nodes in the industrial chain and the position of level 2 nodes in the industrial chain are in the upstream links, such as raw material supply, core technology research and development or high-end design services. The position of level 1 nodes in the industrial chain is better than the position of level 2 nodes in the industrial chain.

[0035] Among them, the position of level 3 nodes in the industrial chain and the position of level 4 nodes in the industrial chain are in the midstream links, and the position of level 3 nodes in the industrial chain is better than the position of level 4 nodes in the industrial chain.

[0036] Among them, other nodes are located in the downstream links of the industrial chain.

[0037] Upstream link: usually refers to the industry at the beginning of the entire industrial chain that provides raw materials and parts manufacturing and production.

[0038] Midstream link: between the upstream and downstream, mainly responsible for processing, assembling or designing the raw materials and parts provided by the upstream link to form semi-finished products or finished products.

[0039] Downstream link: Located at the end of the entire industrial chain, it is mainly responsible for deep processing, modification or packaging of semi-finished products or finished products provided by the midstream, and ultimately transforming them into actual products in production and life.

[0040] Among them, the score corresponding to the node position can clearly reflect the relative position and importance of the current enterprise in the industrial chain, which is conducive to determining the current enterprise's own advantages.

[0041] S23, storing the scores corresponding to the industry fit and the scores corresponding to the node positions, and obtaining the patent scores and copyright scores based on the innovation information; S24, storing the patent score and the copyright score, obtaining the number of branches and the number of abnormal operations in the business information, obtaining the score corresponding to the number of branches, and obtaining the score corresponding to the number of abnormal operations; The storing of the patent score and the copyright score, obtaining the number of branches and the number of abnormal operations in the business information, obtaining the score corresponding to the number of branches, and obtaining the score corresponding to the number of abnormal operations include: Read the second storage instruction, execute the second storage instruction, store the patent score and the copyright score, and obtain a second storage result; When the status identifier in the second storage result is a success identifier, the number of branches and the number of operating abnormalities in the operating information are obtained, and the score corresponding to the number of branches is obtained according to the first score table, and the score corresponding to the number of operating abnormalities is obtained according to the second score table.

[0042] Among them, the first score table is as follows: The number of enterprise branches>10; the score is 10 points; 5<Number of branches of the enterprise<=10; score is 8 points; 0<Number of enterprise branches<=5; score is 6 points; Number of enterprise branches = 0; score is 1 point.

[0043] Among them, the second score table is as follows: Number of operating anomalies = 0; score is 15 points.

[0044] 0<Number of abnormal operations<=5; score is 10 points; 5<Number of abnormal operations<=10; score is 6 points; The number of operating anomalies>10; the score is 2 points.

[0045] Among them, the number of abnormal operations refers to the number of enterprises that have been listed in the abnormal operation list by the market supervision and management department due to violations of relevant laws and regulations or failure to perform relevant obligations during the current operation. By counting the number of abnormal operations, we can timely discover the problems and risks of current enterprises, and then take corresponding regulatory measures to protect market order and consumer rights.

[0046] S25, storing the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, obtaining the enterprise label in the growth information, obtaining the score corresponding to the enterprise label, obtaining the tax credit rating and the number of bad judicial records in the credit information, obtaining the score corresponding to the tax credit rating, obtaining the score corresponding to the number of bad judicial records, obtaining the total number of employees in the contribution information, and obtaining the score corresponding to the total number of employees; S26, add up the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees to generate a total score corresponding to the current enterprise, sort the total scores corresponding to each current enterprise in order from large to small, and recommend the current enterprises in the top N positions as the target enterprises of the industrial chain.

[0047] Wherein, N is a positive integer. Preferably, N is 10.

[0048] For the sake of illustration, an example is given below: For example, there are 100 current enterprises, and the total scores corresponding to each current enterprise are ranked from large to small, and the current enterprises ranked 1 to 10 are recommended as target enterprises of the industrial chain.

[0049] For the sake of illustration, an example is given below: For example, there are 1,000 current enterprises, and the total scores corresponding to each current enterprise are ranked from large to small, and the current enterprises ranked 1 to 10 are recommended as target enterprises of the industrial chain.

[0050] Among them, after the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate the total score corresponding to the current enterprise, the total scores corresponding to each current enterprise are sorted in descending order, and the current enterprises in the top N positions are recommended as the target enterprises of the industrial chain, the enterprise recommendation method includes: The enterprise logo of the target enterprise is obtained, a prompt window is created, and the enterprise logo is displayed in the prompt window.

[0051] Among them, displaying the corporate logo through the prompt window is conducive to improving the efficiency of conveying the corporate logo.

[0052] In the embodiment of the present invention, the beneficial effects are in two aspects. On the one hand, the current enterprises ranked in the top N are recommended as the target enterprises of the industrial chain. Since no manual recommendation is required, the recommendation time of the target enterprises of the industrial chain is reduced, which is beneficial to improving the recommendation efficiency of the target enterprises of the industrial chain. On the other hand, since it will not be affected by manual intervention, it is beneficial to improve the reliability of the target enterprises.

[0053] See also Figure 3 , Figure 3 yes Figure 2 A specific implementation flow diagram of step S23 is described in detail as follows: S31, reading a first storage instruction, executing the first storage instruction, storing the score corresponding to the industry fit and the score corresponding to the node position, and obtaining a first storage result; S32, when the status mark in the first storage result is a success mark, obtaining the total number of patents and the total number of software copyrights in the innovation information; S33, according to the total number of patents, the number of insured persons and the first model, the number of patents owned by every 100 persons is obtained, according to the corresponding relationship between the number of patents owned by every 100 persons and the score, the score corresponding to the number of patents owned by every 100 persons is obtained, and the score corresponding to the number of patents owned by every 100 persons is selected as the patent score; Among them, the first model is: the number of patents owned by every 100 people = (total number of patents ÷ number of insured persons) × 100; Among them, the corresponding relationship between the number of patents owned by every 100 people and the score is as follows: 1. The number of patents per 100 people is greater than 7, 10 points; 2.3<Number of patents per 100 people<=7, 8 points; 3. 0<number of patents per 100 people<=3, 5 points; 4. The number of patents owned per 100 people = 0, so 0 points will be awarded.

[0054] For the sake of illustration, an example is given below: For example, the number of insured persons is 476, and the number of invention patents is 33; The number of patents owned by every 100 people = 33 ÷ 476 × 100 = 6.93. Since 3 < 6.93 <= 7, the score for the number of patents owned by every 100 people is 8 points.

[0055] S34, according to the total number of patents, the number of insured persons and the second model, the number of software copyrights owned by every 100 persons is obtained, and according to the corresponding relationship between the number of software copyrights owned by every 100 persons and the score, the score corresponding to the number of software copyrights owned by every 100 persons is obtained, and the score corresponding to the number of software copyrights owned by every 100 persons is selected as the copyright score; Among them, the second model is: the number of software copyrights owned by every 100 people = (total number of software copyrights ÷ number of insured persons) × 100.

[0056] Among them, the corresponding relationship between the number of patents owned by every 100 people and the score is as follows: 1. If the number of software copyrights owned by every 100 people is greater than 2, 10 points will be awarded; 2. 0 < the number of software copyrights owned by every 100 people <= 2, 8 points; The number of software copyrights owned by every 100 people = 0, and 0 points are awarded; For the sake of illustration, an example is given below: For example, the number of insured persons is 476, and the number of invention patents is 10; The number of software copyrights owned by every 100 people = 10 ÷ 476 × 100 = 2.1. Since 2.1>2, the score for the number of software copyrights owned by every 100 people is 10 points.

[0057] Among them, the more patents and software copyrights owned per 100 people, the stronger the current company has in technology exploration and product iteration.

[0058] In the embodiment of the present invention, when the status indicator in the first storage result is a success indicator, This means that the scores corresponding to the industry fit and the scores corresponding to the node positions have been completely saved in the designated storage area, ensuring the integrity and availability of the scores corresponding to the industry fit and the scores corresponding to the node positions.

[0059] In the embodiment of the present invention, the score corresponding to the number of patents owned by every 100 people is selected as the patent score, and the score corresponding to the number of software copyrights owned by every 100 people is selected as the copyright score, which speeds up the acquisition of patent scores and copyright scores.

[0060] See also Figure 4 , Figure 4 yes Figure 2 A specific implementation flow diagram of step S25 is described in detail as follows: S41, reading a third storage instruction, executing the third storage instruction, storing the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, and obtaining a third storage result; Among them, the first storage instruction, the second storage instruction and the third storage instruction are different storage instructions.

[0061] S42, when the status identifier in the third storage result is a success identifier, obtain the enterprise label in the growth information, obtain the score corresponding to the enterprise label according to the third score table, obtain the score corresponding to the tax credit rating according to the fourth score table, obtain the score corresponding to the number of bad judicial records according to the fifth score table, obtain the total number of employees in the contribution information, and obtain the score corresponding to the total number of employees according to the sixth score table.

[0062] Among them, the third score table is as follows: The corporate label is the label of a listed company or a Fortune 500 company; the score is 20 points; The enterprise label is the unicorn label or the small giant label; the score is 15 points; The enterprise label is the label of a high-tech enterprise or a specialized and innovative enterprise; the score is 10 points; The Enterprise tag is an additional tag and is scored 5 points.

[0063] Other labels refer to labels of other companies.

[0064] Other enterprises refer to enterprises other than listed companies, Fortune 500 companies, unicorns, small giants, high-tech enterprises, and specialized and new enterprises.

[0065] Among them, unicorn companies usually refer to those unlisted companies that have been established for a short time but have a valuation of more than 1 billion US dollars.

[0066] Among them, small giant enterprises refer to leading enterprises that focus on niche markets, have strong innovation capabilities, high market share, master key core technologies, and have excellent quality and efficiency.

[0067] Among them, high-tech enterprises, namely national high-tech enterprises, refer to enterprises in the field of high-tech that are key supported by the state.

[0068] Among them, specialized, sophisticated and innovative enterprises refer to small and medium-sized enterprises with specialization, refinement, distinctiveness and novelty in development characteristics.

[0069] Among them, the fourth score table is as follows: Tax credit rating A; score is 6 points; Tax credit rating B; score is 5 points; Tax credit rating C; score is 4 points; Tax credit rating D; score is 3 points; Among them, tax credit rating is a credit rating evaluation conducted by the tax authorities based on the comprehensive performance of the current enterprise in tax law compliance within a certain tax cycle.

[0070] Among them, tax credit rating A is the highest credit rating, and tax credit rating D is the lowest credit rating.

[0071] Among them, the fifth score table is as follows: The number of adverse judicial records <= 0; the score is 4 points; 0<Number of adverse judicial records<=5; score is 3 points; 5 <Number of adverse judicial records <= 10; score is 2 points; The number of adverse judicial records is greater than 10; the score is 1 point; Among them, the number of bad judicial records refers to the number of records of bad behavior or illegal behavior of the current enterprise at the legal level. The more bad judicial records there are, the lower the trust and the lower the score. The fewer bad judicial records there are, the higher the trust and the higher the score.

[0072] Among them, the sixth score table is as follows: 0<total number of employees<=20, score 1; 20<total number of employees<=100, score is 2 points; 100<total number of employees<=500, score is 4 points; 500 < total number of employees, score is 5 points.

[0073] In an embodiment of the present invention, when the status identifier in the third storage result is a success identifier, it means that the scores corresponding to the number of branches and the scores corresponding to the number of business abnormalities have been completely saved in the designated storage area, ensuring the integrity and availability of the scores corresponding to the number of branches and the scores corresponding to the number of business abnormalities.

[0074] See also Figure 5 , Figure 5 yes Figure 2 A specific implementation flow diagram of step S26 is described in detail as follows: S51, using a preset total score generation model, the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate a total score corresponding to the current enterprise; Exemplarily, the total score generation model is: F=(F1+F2)×W1+(F3+F4)×W1+(F5+F6)×W3+F7×W4+(F8+F9)×W5+F10×W6; Among them, F is the total score, F1 is the score corresponding to the industry fit, F2 is the score corresponding to the node position, and W1 is the first weight value; Among them, F3 is the patent score, F4 is the copyright score, and W1 is the second weight value; Among them, F5 is the score corresponding to the number of branches, F6 is the score corresponding to the number of abnormal operations, and W3 is the third weight value; Among them, F7 is the score corresponding to the enterprise label, and W4 is the fourth weight value; Among them, F8 is the score corresponding to the tax credit rating, F9 is the score corresponding to the number of bad judicial records, and W5 is the fifth weight value; Among them, F10 is the score corresponding to the total number of employees, W6 is the sixth weight value, and the sum of W1, W2, W3, W4, W5, and W6 is 1.

[0075] S52, reading the sorting instruction in the register, and sorting the total score corresponding to each of the current enterprises in descending order according to the sorting instruction, and recommending the top 10 current enterprises as target enterprises of the industrial chain.

[0076] Among them, the total score corresponding to the current enterprise is generated through a preset total score generation model. Since the total score integrates multiple dimensions of the current enterprise's industrial information, innovation information, business information, growth information, credit information, contribution information, etc., the higher the total score, the stronger the comprehensive strength of the current enterprise in the industrial chain. The current enterprises ranked in the top 10 are recommended as target enterprises of the industrial chain. This not only improves the recommendation accuracy of the target enterprises, but also improves the recommendation efficiency of the target enterprises.

[0077] In an embodiment of the present invention, a sorting instruction in a register is read, and the total score corresponding to each of the current enterprises is sorted in descending order through the sorting instruction, and the top 10 current enterprises are recommended as target enterprises of the industrial chain. Since no manual recommendation is required, the recommendation time of the target enterprises of the industrial chain is reduced, which is conducive to improving the recommendation efficiency of the target enterprises of the industrial chain.

[0078] See also Figure 6 , Figure 6 : is a schematic diagram of a structure of an enterprise recommendation device in one embodiment of the present invention, such as Figure 6As shown, the enterprise recommendation device includes a first acquisition module 101, a second acquisition module 102, a third acquisition module 103, a fourth acquisition module 104, a fifth acquisition module 105, and a recommendation module 106. The functional modules are described in detail as follows: The first acquisition module 101 is used to acquire the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information; The second acquisition module 102 is used to obtain the industry fit degree and the position of the current enterprise in the industrial chain in the industrial information, select the position of the current enterprise in the industrial chain as the node position, and obtain the score corresponding to the industry fit degree and the score corresponding to the node position; The third acquisition module 103 is used to store the scores corresponding to the industry fit and the scores corresponding to the node positions, and acquire the patent scores and copyright scores based on the innovation information; The fourth acquisition module 104 is used to store the patent score and the copyright score, obtain the number of branches and the number of abnormal operations in the business information, obtain the score corresponding to the number of branches, and obtain the score corresponding to the number of abnormal operations; The fifth acquisition module 105 is used to store the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, obtain the enterprise label in the growth information, obtain the score corresponding to the enterprise label, obtain the tax credit rating and the number of bad judicial records in the credit information, obtain the score corresponding to the tax credit rating, obtain the score corresponding to the number of bad judicial records, obtain the total number of employees in the contribution information, and obtain the score corresponding to the total number of employees; The recommendation module 106 is used to add the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees to generate a total score corresponding to the current enterprise, sort the total scores corresponding to each of the current enterprises in order from large to small, and recommend the current enterprises in the top N positions as the target enterprises of the industrial chain.

[0079] In the embodiment of the present invention, the beneficial effects are in two aspects. On the one hand, the current enterprises ranked in the top N are recommended as the target enterprises of the industrial chain. Since no manual recommendation is required, the recommendation time of the target enterprises of the industrial chain is reduced, which is beneficial to improving the recommendation efficiency of the target enterprises of the industrial chain. On the other hand, since it will not be affected by manual intervention, it is beneficial to improve the reliability of the target enterprises.

[0080] For the specific limitations of the enterprise recommendation device, please refer to the limitations of the enterprise recommendation method above, which will not be repeated here.

[0081] Each module in the above-mentioned enterprise recommendation device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0082] See also Figure 7 , Figure 7 1 is another structural diagram of a computer device in one embodiment of the present invention. In one embodiment, a computer device is provided. The computer device is a server device or a client device. The internal structure diagram thereof can be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external database. When the computer program is executed by the processor, the functions or steps of an enterprise recommendation method of an industrial chain can be realized.

[0083] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor.

[0084] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant description of the aforementioned method embodiment. In order to avoid repetition, they will not be described one by one here.

[0085] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. Technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. Technicians can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

Claims

1. A method for recommending enterprises in an industrial chain, characterized in that: include: Obtain the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information; Obtaining the industry fit degree and the position of the current enterprise in the industry chain in the industry information, selecting the position of the current enterprise in the industry chain as the node position, and obtaining the score corresponding to the industry fit degree and the score corresponding to the node position; The scores corresponding to the industry fit and the node position are stored, and the patent score and copyright score are obtained based on the innovation information; The patent score and the copyright score are stored, the number of branches and the number of abnormal operations in the business information are obtained, the score corresponding to the number of branches is obtained, and the score corresponding to the number of abnormal operations is obtained; The scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations are stored, the enterprise label in the growth information is obtained, the score corresponding to the enterprise label is obtained, the tax credit rating and the number of bad judicial records in the credit information are obtained, the score corresponding to the tax credit rating is obtained, the score corresponding to the number of bad judicial records is obtained, the total number of employees in the contribution information is obtained, and the score corresponding to the total number of employees is obtained; The scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate the total score corresponding to the current enterprise. The total scores corresponding to each current enterprise are sorted in descending order, and the current enterprises in the top N positions are recommended as the target enterprises of the industrial chain.

2. The enterprise recommendation method according to claim 1, characterized in that: The obtaining of the industry fit degree in the industry information and the position of the current enterprise in the industry chain, selecting the position of the current enterprise in the industry chain as the node position, and obtaining the score corresponding to the industry fit degree and the score corresponding to the node position include: Analyze the industrial information, and obtain the industrial fit and the position of the current enterprise in the industrial chain from the analyzed industrial information; Select the current enterprise's position in the industrial chain as the node position, obtain the score corresponding to the industry fit, and obtain the score corresponding to the node position.

3. The enterprise recommendation method according to claim 1, characterized in that: The scores corresponding to the industry fit and the scores corresponding to the node positions are stored, and the patent scores and copyright scores are obtained based on the innovation information, including: Reading the first storage instruction, executing the first storage instruction, storing the score corresponding to the industry fit and the score corresponding to the node position, and obtaining a first storage result; When the status mark in the first storage result is a success mark, obtaining the total number of patents and the total number of software copyrights in the innovation information; According to the total number of patents, the number of insured persons and the first model, the number of patents owned by every 100 persons is obtained. According to the corresponding relationship between the number of patents owned by every 100 persons and the score, the score corresponding to the number of patents owned by every 100 persons is obtained, and the score corresponding to the number of patents owned by every 100 persons is selected as the patent score; According to the total number of patents, the number of insured persons and the second model, the number of software copyrights owned by every 100 persons is obtained, and according to the corresponding relationship between the number of software copyrights owned by every 100 persons and the score, the score corresponding to the number of software copyrights owned by every 100 persons is obtained, and the score corresponding to the number of software copyrights owned by every 100 persons is selected as the copyright score; Among them, the first model is: the number of patents owned by every 100 people = (total number of patents ÷ number of insured persons) × 100; Among them, the second model is: the number of software copyrights owned by every 100 people = (total number of software copyrights ÷ number of insured persons) × 100.

4. The enterprise recommendation method according to claim 1, characterized in that: The storing of the patent score and the copyright score, obtaining the number of branches and the number of abnormal operations in the business information, obtaining the score corresponding to the number of branches, and obtaining the score corresponding to the number of abnormal operations include: Read the second storage instruction, execute the second storage instruction, store the patent score and the copyright score, and obtain a second storage result; When the status identifier in the second storage result is a success identifier, the number of branches and the number of operating abnormalities in the operating information are obtained, and the score corresponding to the number of branches is obtained according to the first score table, and the score corresponding to the number of operating abnormalities is obtained according to the second score table.

5. The enterprise recommendation method according to claim 1, characterized in that: The storing of the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, obtaining the enterprise label in the growth information, obtaining the score corresponding to the enterprise label, obtaining the tax credit rating and the number of bad judicial records in the credit information, obtaining the score corresponding to the tax credit rating, obtaining the score corresponding to the number of bad judicial records, obtaining the total number of employees in the contribution information, and obtaining the score corresponding to the total number of employees includes: Reading a third storage instruction, executing the third storage instruction, storing the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, and obtaining a third storage result; When the status identifier in the third storage result is a success identifier, obtain the enterprise label in the growth information, obtain the score corresponding to the enterprise label according to the third score table, obtain the score corresponding to the tax credit rating according to the fourth score table, obtain the score corresponding to the number of bad judicial records according to the fifth score table, obtain the total number of employees in the contribution information, and obtain the score corresponding to the total number of employees according to the sixth score table.

6. The enterprise recommendation method according to claim 1, characterized in that: The score corresponding to the industry fit, the score corresponding to the node position, the patent score, the copyright score, the score corresponding to the enterprise label, the score corresponding to the tax credit rating, the score corresponding to the number of bad judicial records, and the score corresponding to the total number of employees are added together to generate a total score corresponding to the current enterprise, and the total score corresponding to each current enterprise is sorted in order from large to small, and the current enterprises in the top N positions are recommended as the target enterprises of the industrial chain, including: Through the preset total score generation model, the scores corresponding to the industry fit, the scores corresponding to the node position, the patent score, the copyright score, the score corresponding to the enterprise label, the score corresponding to the tax credit rating, the score corresponding to the number of bad judicial records, and the score corresponding to the total number of employees are added together to generate the total score corresponding to the current enterprise; The sorting instruction in the register is read, and the total score corresponding to each current enterprise is sorted in descending order according to the sorting instruction, and the top 10 current enterprises are recommended as target enterprises of the industrial chain.

7. The enterprise recommendation method according to claim 1, characterized in that: After the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees are added together to generate the total score corresponding to the current enterprise, the total scores corresponding to each current enterprise are sorted in descending order, and the current enterprises in the top N positions are recommended as the target enterprises of the industrial chain, the enterprise recommendation method includes: The enterprise logo of the target enterprise is obtained, a prompt window is created, and the enterprise logo is displayed in the prompt window.

8. An enterprise recommendation device for an industrial chain, characterized in that: include: The first acquisition module is used to obtain the current enterprise's industry information, innovation information, business information, growth information, credit information, and contribution information; The second acquisition module is used to obtain the industry fit degree and the position of the current enterprise in the industrial chain in the industrial information, select the position of the current enterprise in the industrial chain as the node position, and obtain the score corresponding to the industry fit degree and the score corresponding to the node position; The third acquisition module is used to store the scores corresponding to the industry fit and the scores corresponding to the node positions, and obtain the patent scores and copyright scores based on the innovation information; A fourth acquisition module is used to store the patent score and the copyright score, obtain the number of branches and the number of abnormal operations in the business information, obtain the score corresponding to the number of branches, and obtain the score corresponding to the number of abnormal operations; A fifth acquisition module is used to store the scores corresponding to the number of branches and the scores corresponding to the number of abnormal operations, obtain the enterprise label in the growth information, obtain the score corresponding to the enterprise label, obtain the tax credit rating and the number of bad judicial records in the credit information, obtain the score corresponding to the tax credit rating, obtain the score corresponding to the number of bad judicial records, obtain the total number of employees in the contribution information, and obtain the score corresponding to the total number of employees; The recommendation module is used to add the scores corresponding to the industry fit, the scores corresponding to the node positions, the patent scores, the copyright scores, the scores corresponding to the enterprise labels, the scores corresponding to the tax credit ratings, the scores corresponding to the number of bad judicial records, and the scores corresponding to the total number of employees to generate a total score corresponding to the current enterprise, sort the total scores corresponding to each current enterprise in order from large to small, and recommend the current enterprises in the top N positions as the target enterprises of the industrial chain.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the enterprise recommendation method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the enterprise recommendation method according to any one of claims 1 to 7 are implemented.

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