A business matchmaking method, apparatus, device and medium

Abstract

This invention discloses a method, apparatus, device, and medium for enterprise matching, relating to the field of artificial intelligence and applicable to the fintech field. The method includes: completing the original information generated by a target enterprise on a matching platform to obtain complete enterprise information; generating an enterprise profile of the target enterprise based on the complete enterprise information; and determining a matching score between the target enterprise and other target enterprises based on the enterprise profile of the target enterprise and the enterprise profiles of other target enterprises. Embodiments of this invention can achieve accurate enterprise matching.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence and can be used in the field of financial technology, particularly to a business matching method, apparatus, equipment, and medium. Background Technology

[0002] A bank's business matchmaking platform is an online service platform designed to help corporate clients find partners, products, and services more efficiently. On one hand, the platform guides companies to register their products and needs online for other clients on the platform to browse, allowing companies to spontaneously find matches. On the other hand, it can undertake various online and offline business activities, inviting a large number of companies and guiding them to one-on-one negotiations through manual matching, ultimately facilitating successful deals.

[0003] However, both methods rely heavily on users' manual and spontaneous creation, depending on their initiative. At the same time, because the platform's enterprise profiles only rely on limited data actively filled in by users (i.e., the products and needs mentioned above), and lack supplementary multi-dimensional external information (such as publicly available company size and industry dynamics), the matching basis is insufficient, resulting in low matching accuracy. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and medium for matching businesses, in order to achieve accurate matching of businesses.

[0005] According to one aspect of the present invention, a business matching method is provided, comprising:

[0006] The original information generated by the target company on the matching platform is supplemented to obtain the complete company information of the target company.

[0007] Generate a corporate profile of the target company to be matched based on the complete corporate information;

[0008] Based on the corporate profile of the target company to be matched and the corporate profiles of other companies to be matched, the matching score of the target company to be matched and other companies to be matched is determined.

[0009] According to another aspect of the present invention, a business matching device is provided, comprising:

[0010] The completion module is used to complete the original information generated by the target company on the matching platform to obtain the complete company information of the target company.

[0011] The generation module is used to generate a corporate profile of the target company to be matched based on the complete corporate information.

[0012] The determination module is used to determine the matching score between the target company to be matched and other companies to be matched based on the company profile of the target company to be matched and the company profiles of other companies to be matched.

[0013] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the enterprise matching method according to any embodiment of the present invention.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the enterprise matching method according to any embodiment of the present invention.

[0015] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the enterprise matching method according to any embodiment of the present invention.

[0016] This invention overcomes the limitations of traditional platforms that rely on user-submitted data, integrates internal and external platform information, avoids mismatches caused by information discrepancies, and significantly improves the success rate of intelligent recommendations.

[0017] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of a business matching method according to an embodiment of the present invention;

[0020] Figure 2 This is a flowchart of a business matching method provided according to another embodiment of the present invention;

[0021] Figure 3 This is a schematic diagram of the structure of a business matching device according to another embodiment of the present invention;

[0022] Figure 4 This is a schematic diagram of the structure of an electronic device that implements an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first," "second," etc., used in this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] Figure 1 This is a flowchart illustrating a business matching method according to an embodiment of the present invention. This embodiment is applicable to situations where banks match businesses using their own matching platforms. The method can be executed by a business matching device, which can be implemented in hardware and / or software. This device can be configured in an electronic device with corresponding data processing capabilities, such as a bank's matching platform. Figure 1 As shown, the method includes:

[0026] S110. Complete the original information generated by the target company on the matching platform to obtain the complete company information of the target company.

[0027] S120. Generate a corporate profile of the target company to be matched based on the complete corporate information.

[0028] S130. Based on the enterprise profile of the target enterprise to be matched and the enterprise profiles of other enterprises to be matched, determine the matching score between the target enterprise to be matched and other enterprises to be matched.

[0029] Specifically, the process involves acquiring raw information generated by the target company during its registration and use of the matchmaking platform. This includes basic company information entered during registration, behavioral data, interaction data, and preferences set on the platform. Simultaneously, it involves accessing legitimate public information sources outside the platform, such as the company's official website, Tianyancha (a Chinese business information platform), and the customs import / export disclosure platform, and collecting relevant information about the target company. These two types of information are then aggregated to obtain complete company information for the target company, and a company profile is generated based on this complete information. For other companies seeking matchmaking, customer profiles can be generated directly based on their raw information generated on the platform; alternatively, like the target company, the raw information can be supplemented before generating a company profile. The company profiles of other companies are then matched one by one with the target company's company profile to obtain a matching score. Subsequently, companies recommended to the target company are selected from the other companies based on their matching scores.

[0030] This invention overcomes the limitations of traditional platforms that rely on user-submitted data, integrates internal and external platform information, avoids mismatches caused by information discrepancies, and significantly improves the success rate of intelligent recommendations.

[0031] Based on the above embodiments, optionally, the original information includes the basic enterprise information filled in by the enterprise when registering on the matching platform, behavioral data on the matching platform, interaction data on the matching platform, and preferences set on the matching platform.

[0032] Specifically, the basic information filled in during company registration includes: company logo, company name, company name (English), company type, country / region, establishment date, detailed address, contact information, company video, Chinese introduction, English introduction, and image materials submitted during the application. Data includes page click data (e.g., clicks on page buttons, heatmaps, recording the frequency and duration of the company's browsing of modules such as "Global Business Opportunities" and "Featured Zones") and activity data (e.g., monthly login frequency, online meeting records participated in through the matching platform, and offline exhibition check-in data). Interaction data refers to the data on the interaction between the company and other companies on the matching platform, including the number of times cooperation intentions were sent, historical negotiation records, ratings based on "cooperation satisfaction" feedback from both parties, and ratings after participating in activities. Preferences include two types of data: first, fixed preference information such as industry category, supply and demand category, and intention category regularly maintained by the company; second, key value information published by the company through Natural Language Processing (NLP) analysis and extraction, such as "prioritizing suppliers in the Yangtze River Delta" and "accepting payment terms financing." By collecting multi-dimensional raw information that includes operational capabilities, industry characteristics, and cooperation preferences, the accuracy of enterprise profiles in describing enterprises can be improved.

[0033] For example, the content of basic enterprise information is shown in Table 1 below, the content of enterprise preferences is shown in Table 2 below, and the content of behavioral data is shown in Table 3 below.

[0034] Table 1: Basic Information of Enterprises

[0035]

[0036] Table 2: Enterprise Preference Table

[0037]

[0038]

[0039] Table 3: Behavioral Data Table

[0040]

[0041] Figure 2 This is a flowchart illustrating a business matching method according to another embodiment of the present invention. This embodiment is an optimization and improvement upon the above embodiment. Figure 2 As shown, the method includes:

[0042] S210. Based on the original information generated by the target company on the matching platform, collect relevant information about the target company from an external platform; merge the relevant information and the original information to obtain complete company information of the target company.

[0043] Specifically, when certain triggering conditions are met, such as when a company logs in or performs important functions / actions, the platform accesses legitimate and publicly available data sources, such as the company's official website and customs import / export disclosure platforms, based on the company's basic information. This data collects relevant information about the target company to be matched, including its operational dynamics (e.g., latest winning bids, patent authorization records, changes in job postings reflecting capacity expansion); its supply chain relationships (e.g., identifying potential partners through equity structure diagrams and publicly tendered contracts); and public opinion data (e.g., frequency of mentions on social media, positive / negative sentiment analysis of news articles for risk assessment). The relevant and raw information is then aggregated and merged, filtering out invalid data to obtain complete company information for the target company. Expanding information sources further enhances the reference value of the company information.

[0044] Based on the above embodiments, optionally, the step of merging the relevant information and the original information to obtain the complete enterprise information of the target matching enterprise includes:

[0045] The large model is invoked to analyze whether there is a conflict between the relevant information and the original information;

[0046] If a conflict exists, the relevant information or the original information shall be determined as the complete enterprise information based on the source of the information;

[0047] If it does not exist, both the relevant information and the original information will be determined as complete enterprise information.

[0048] Specifically, after anonymizing relevant and original information, it is input into a locally deployed large-scale model. The model is given corresponding task prompts, requiring it to analyze whether there are any conflicting information between the relevant and original information. Based on this, the model compares and analyzes the input relevant and original information, and outputs the conflicting information, such as "external information shows a registered capital of 50 million, while internal information shows a registered capital of 30 million." For conflicting information, the more credible information is selected as the complete enterprise information. For non-conflicting information, no selection is needed, and both are directly used as complete enterprise information. By cross-validating information from both inside and outside the platform, the matching process can be prevented from being affected by invalid or erroneous information.

[0049] Based on the above embodiments, optionally, determining the relevant information or the original information as complete enterprise information according to the information source includes:

[0050] If the priority of the information source of the aforementioned relevant information is not higher than the priority of the matching platform, then the original information will be determined as complete enterprise information;

[0051] If the information source of the relevant information has a higher priority than the matching platform, then the relevant information will be identified as complete enterprise information.

[0052] Specifically, different information sources are prioritized in advance. For conflicting information, credibility is determined by comparing their sources. If the priority of the information source is no higher than that of the matching platform, the original information is identified as complete company information. For example, if the information about a registered capital of 50 million comes from an interview with a company leader, and the priority of this interview is no higher than that of the matching platform, then the information about a registered capital of 30 million is identified as complete company information. Conversely, if the priority of the information source is higher than that of the matching platform, then the information about a registered capital of 50 million comes from publicly available information from the business registration authority, and the business registration authority has a higher priority than the matching platform, then the information about a registered capital of 50 million is identified as complete company information. By prioritizing information sources and filtering invalid information based on these priorities, manual verification is eliminated, improving the efficiency of verifying conflicting information.

[0053] S220. Generate a corporate profile of the target company to be matched based on the complete corporate information; determine a set of indicator weights associated with the industry to which the target company to be matched belongs.

[0054] S230. Calculate the matching score between the corporate profile of the target company to be matched and the corporate profiles of other companies to be matched, based on the weights of the indicators in this group.

[0055] Specifically, for matching enterprise profiles, assigning different weights to different matching indicators is a common practice. However, in enterprise matching scenarios, different industries have different priorities. In the traditional civil engineering industry, companies value the size of the partner company to ensure that construction progress is not interrupted by funding issues; in the new energy industry, companies value the technological capabilities of the partner company to ensure that product iteration and R&D can lead the industry. Therefore, the platform pre-sets a set of indicator weights for each industry based on its characteristics. For example, for the real estate industry, the weight of the enterprise rules indicator is 30%, and the weight of the number of technology patents indicator is 1%; while in the new energy industry, the weight of the enterprise rules indicator is 10%, and the weight of the number of technology patents indicator is 15%. When matching enterprise profiles, based on the industry of the target enterprise, a set of indicator weights associated with that industry is determined from multiple pre-stored sets of indicator weights. The matching scores of the target enterprise's profile and the enterprise profiles of other enterprises are calculated on each indicator, and these matching scores are weighted and summed using the indicator weights to obtain the final matching score. Furthermore, users can manually enable or disable certain calculation factors on the platform for different scenarios. For example, in a conference setting where there are few selectable companies, the scoring logic for factors such as location can be disabled, and the weight of real-time interactive data, such as the intention data of individuals proactively initiating invitations within the conference venue, can be increased. By setting different indicator weights for different industries, the accuracy of matching score calculations is improved.

[0056] S240. Sort the other companies to be matched in descending order of matching score, and determine the other companies to be matched at the top of the ranking as the matching companies recommended to the target company to be matched.

[0057] S250. If the success rate of this matchmaking is lower than the success rate threshold, a weight analysis report is generated based on the weight of the set of indicators and the matching score, and the weight analysis report is pushed to the administrator of the matchmaking platform.

[0058] Specifically, other companies awaiting matchmaking are sorted in descending order of their matching scores. The top 10 companies (e.g., the first 10) are then recommended to the target company. After each matchmaking round, the company booth status is manually updated. When a company leaves the booth, the following process is triggered: update the list of companies present → recalculate the matching score based on the remaining companies' profiles → push a new matching plan to the organizer's terminal. After the matchmaking ends, feedback from participating companies is collected, and the success rate of the matchmaking is calculated. A reinforcement learning model is introduced to generate evaluation reports for staff periodically based on the success rate feedback. Indicators with excessively high weights and their corresponding matching scores are highlighted to avoid over-concentration of recommended companies within the same industry segment, enabling dynamic adjustment of weight settings.

[0059] This invention improves the accuracy of matching score calculation by setting different indicator weights for different industries.

[0060] Figure 3 This is a schematic diagram of a business matching device provided in another embodiment of the present invention. Figure 3 As shown, the device includes:

[0061] The completion module 310 is used to complete the original information generated by the target company to be matched on the matching platform to obtain the complete company information of the target company to be matched.

[0062] The generation module 320 is used to generate a corporate profile of the target company to be matched based on the complete corporate information.

[0063] The determination module 330 is used to determine the matching score between the target company to be matched and other companies to be matched based on the company profile of the target company to be matched and the company profiles of other companies to be matched.

[0064] The business matching device provided in the embodiments of the present invention can execute the business matching method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0065] Optionally, the completion module 310 includes:

[0066] The data acquisition unit is used to collect relevant information about the target company to be matched from an external platform based on the original information generated by the target company on the matching platform.

[0067] The merging unit is used to merge the relevant information and the original information to obtain complete enterprise information of the target enterprise to be matched.

[0068] Optionally, the merging unit includes:

[0069] The analysis subunit is used to call the large model to analyze whether there is a conflict between the relevant information and the original information;

[0070] The filtering subunit is used to determine the relevant information or the original information as complete enterprise information based on the information source if a conflict exists.

[0071] Merge sub-units to determine that both relevant and original information are complete enterprise information if there are no conflicts.

[0072] Optionally, the filtering subunit is specifically used to: call the large model to analyze whether there is a conflict between the relevant information and the original information; if there is a conflict, determine the relevant information or the original information as complete enterprise information according to the information source; if there is no conflict, determine both the relevant information and the original information as complete enterprise information.

[0073] Optionally, the original information includes the basic information of the enterprise that it fills in when registering on the matching platform, behavioral data on the matching platform, interaction data on the matching platform, and preferences set on the matching platform.

[0074] Optionally, the determining module 330 includes:

[0075] The determining unit is used to determine a set of indicator weights associated with the target company to be matched, based on the industry to which the target company belongs.

[0076] The calculation unit is used to calculate the matching score between the enterprise profile of the target enterprise to be matched and the enterprise profile of other enterprises to be matched, based on the weight of the set of indicators.

[0077] Optionally, the device further includes:

[0078] The sorting module is used to sort other companies to be matched in descending order of matching score, and to identify the other companies to be matched at the top of the sort as the matching companies recommended to the target company to be matched.

[0079] The feedback module is used to generate a weight analysis report based on the weights of the set of indicators and the matching score if the success rate of the current match is lower than the success rate threshold, and to push the weight analysis report to the administrators of the matchmaking platform.

[0080] The enterprise matching device described in further detail can also execute the enterprise matching method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0081] Figure 4A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0082] like Figure 4 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded into the RAM 43 from storage unit 48. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0083] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0084] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as enterprise matching methods.

[0085] In some embodiments, the business matching method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the business matching method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to perform the business matching method by any other suitable means (e.g., by means of firmware).

[0086] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0087] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0088] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0089] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0090] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0091] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0092] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0093] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for facilitating business matching, characterized in that, The method includes: The original information generated by the target company on the matching platform is supplemented to obtain the complete company information of the target company. Generate a corporate profile of the target company to be matched based on the complete corporate information; Based on the corporate profile of the target company to be matched and the corporate profiles of other companies to be matched, the matching score of the target company to be matched and other companies to be matched is determined.

2. The method according to claim 1, characterized in that, The process of supplementing the original information generated by the target company on the matching platform to obtain the complete company information of the target company includes: Based on the original information generated by the target company on the matching platform, relevant information about the target company is collected from external platforms. The relevant information and the original information are combined to obtain the complete enterprise information of the target enterprise to be matched.

3. The method according to claim 2, characterized in that, The process of merging the relevant information and the original information to obtain the complete enterprise information of the target enterprise to be matched includes: The large model is invoked to analyze whether there is a conflict between the relevant information and the original information; If a conflict exists, the relevant information or the original information shall be determined as the complete enterprise information based on the source of the information; If there is no conflict, both the relevant information and the original information will be identified as complete enterprise information.

4. The method according to claim 3, characterized in that, The step of determining the relevant information or the original information as complete enterprise information based on the information source includes: If the priority of the information source of the aforementioned relevant information is not higher than the priority of the matching platform, then the original information will be determined as complete enterprise information; If the information source of the relevant information has a higher priority than the matching platform, then the relevant information will be identified as complete enterprise information.

5. The method according to any one of claims 1-4, characterized in that, The original information includes the basic information of the enterprise when registering on the matching platform, the behavioral data on the matching platform, the interaction data on the matching platform, and the preferences set on the matching platform.

6. The method according to claim 1, characterized in that, The step of determining the matching score between the target company and other companies based on the company profile of the target company and the company profiles of other companies includes: Based on the industry of the target company to be matched, determine a set of indicator weights associated with the industry. The matching score between the corporate profile of the target company to be matched and the corporate profiles of other companies to be matched is calculated based on the weight of this set of indicators.

7. The method according to claim 6, characterized in that, After determining the matching score between the target company and other companies based on their company profiles and those of other companies seeking matching, the process further includes: Other companies awaiting matching are sorted in descending order of matching score, and the companies ranked first are identified as the matching companies recommended to the target company. If the success rate of this matchmaking is lower than the success rate threshold, a weight analysis report will be generated based on the weight of the set of indicators and the matching score, and the weight analysis report will be pushed to the administrators of the matchmaking platform.

8. A business matching device, characterized in that, The device includes: The completion module is used to complete the original information generated by the target company on the matching platform to obtain the complete company information of the target company. The generation module is used to generate a corporate profile of the target company to be matched based on the complete corporate information. The determination module is used to determine the matching score between the target company to be matched and other companies to be matched based on the company profile of the target company to be matched and the company profiles of other companies to be matched.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the business matching method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the enterprise matching method according to any one of claims 1-7.

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