An ai large model-based company industry information analysis and identification system
By using an AI-based large-scale model-based company industry information analysis system, which incorporates preprocessing, matching, and caching modules, and combines the large-scale model with an industry knowledge base, the system solves the problems of low efficiency and insufficient accuracy in existing technologies for matching company industry information, achieving efficient and accurate industry identification and classification.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-19
- Publication Date
- 2026-06-19
AI Technical Summary
Existing company industry information matching systems based on fixed rules cannot meet diverse business needs, resulting in low matching efficiency and large accuracy deviations.
The company industry information analysis system based on AI big data models includes a preprocessing module, a matching and acquisition module, a caching module, and a CC code mapping and output sub-module. It uses big data models such as GPT, Wenxin Yiyan, and Tongyi Qianwen to match and cache company industry information, and combines industry knowledge base for accurate identification.
It improves the efficiency and accuracy of identifying company industry information, avoids the inflexibility of fixed rules, and enables the rapid acquisition of structured industry classification results.
Smart Images
Figure CN122240747A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of computer technology, specifically to a company industry information analysis and identification system based on an AI large-scale model. Background Technology
[0002] Company industry information includes information such as which industry the company belongs to, what business it engages in, and its position within that industry. For corporate lending, analyzing industry trends, company financials, and operating data can help assess a company's capabilities, screen for high-quality targets, and avoid low-quality assets.
[0003] Existing technology platforms that obtain company industry information based on fixed rules may appear to be able to match and obtain company industry information according to the rules, but they are not flexible and have a narrow scope of support, which cannot meet the diverse needs of actual production and the ever-growing business scenarios.
[0004] Based on the above reasons, this invention designs a company industry information analysis and recognition system based on an AI large model. By matching with the AI large model, the company's industry information can be obtained more flexibly, avoiding the problems of low matching efficiency and large accuracy deviation caused by separating the company name and industry under the inherent rules. Summary of the Invention
[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a company industry information analysis and recognition system based on an AI large model. By matching with the AI large model, the industry information of the company can be obtained more flexibly, avoiding the problems of low matching efficiency and large accuracy deviation caused by separating the company name and industry under the inherent rules.
[0006] To achieve the above objectives, the present invention provides a company industry information analysis and identification system based on an AI large model, including a company industry information large model preprocessing module, a company industry information matching and acquisition module, a company industry information caching module, and a CC code mapping and output sub-module. The preprocessing module for the company's industry information big data model includes the acquisition and statistics of company industry information; The company industry information matching and acquisition module includes uploading the company's original data, the company industry information big model preprocessing module matching company industry information based on the preprocessed data set, and the company industry information matching and acquisition module maintaining and optimizing a dedicated prompt word template for interacting with the big model in the company industry information big model preprocessing module. The company industry information caching module persistently stores the original data of the companies that have been matched. When the original data of the same company is matched again, the company's industry information can be obtained without going through the company industry information big model preprocessing module. The CC code mapping and output submodule receives the text analysis results returned by the large model, accurately maps them to a preset, structured industry classification system, and outputs them in a formatted manner.
[0007] The prompt word template guides the company's industry information big data model preprocessing module to make industry judgments based on the company name and industry knowledge base.
[0008] The system's execution logic is as follows: S1, upload the company information that needs to be analyzed and identified; S2, determine whether the original data of the company that has already been matched in the company industry information cache module has been hit; S3, if data is hit in S2, then directly extract the data from the cache and end the recognition process; S4. If no data is found in S2, the identification is completed by accessing the large model in the company industry information large model preprocessing module and obtaining the company industry information through the existing large model data.
[0009] The large models in the preprocessing module of the company's industry information large model are GPT, Wenxin Yiyan, and Tongyi Qianwen.
[0010] Compared with the prior art, the present invention has the following beneficial effects: This invention utilizes the system's caching module in conjunction with the database in the existing big data model to efficiently identify key prompts for industries and companies. This effectively avoids the inflexibility of fixed rules, quickly improves the acquisition of identification results, and provides effective assistance for the identification and analysis of company industry information. Attached Figure Description
[0011] Figure 1 This is a schematic diagram of the execution flow of the system of the present invention. Detailed Implementation
[0012] The present invention will now be further described with reference to the accompanying drawings.
[0013] See Figure 1 This embodiment provides a company industry information analysis and identification system based on an AI large model, including a company industry information large model preprocessing module, a company industry information matching and acquisition module, a company industry information caching module, and a CC code mapping and output sub-module; The preprocessing module for the company's industry information big data model includes the acquisition and statistics of company industry information; The company industry information matching and acquisition module includes uploading the company's original data, the company industry information big model preprocessing module matching company industry information based on the preprocessed data set, and the company industry information matching and acquisition module maintaining and optimizing a dedicated prompt word template for interacting with the big model in the company industry information big model preprocessing module. The company industry information caching module persistently stores the original data of the companies that have been matched. When the original data of the same company is matched again, the company's industry information can be obtained without going through the company industry information big model preprocessing module. The CC code mapping and output submodule receives the text analysis results returned by the large model, accurately maps them to a preset, structured industry classification system, and outputs them in a formatted manner. For example, "This is a financial institution that mainly engages in commercial banking business" is accurately mapped to a preset, structured industry classification code system (e.g., mapping "commercial bank" to "C10") and output in a formatted manner.
[0014] The prompt word template guides the company's industry information big data model preprocessing module to make industry judgments based on the company name and industry knowledge base.
[0015] The system's execution logic is as follows: S1, upload the company information that needs to be analyzed and identified; S2, determine whether the original data of the company that has already been matched in the company industry information cache module has been hit; S3, if data is hit in S2, then directly extract the data from the cache and end the recognition process; S4. If no data is found in S2, the identification is completed by accessing the large model in the company industry information large model preprocessing module and obtaining the company industry information through the existing large model data.
[0016] The large models in the preprocessing module of the company's industry information large model are GPT, Wenxin Yiyan, and Tongyi Qianwen.
[0017] The above are merely preferred embodiments of the present invention, intended only to aid in understanding the method and core ideas of this application. The scope of protection of the present invention is not limited to the above embodiments; all technical solutions falling within the scope of the present invention's concept are within its protection. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.
[0018] This invention comprehensively addresses the shortcomings of existing technologies that rely on fixed rules to obtain company and industry information, resulting in low accuracy and efficiency in recognition. By utilizing the system's caching module in conjunction with the database in the existing big data model, it can efficiently identify key prompts for industries and companies, effectively avoiding the inflexibility of fixed rules, and quickly improving the acquisition of recognition results, thus providing effective assistance for the identification and analysis of company and industry information.
Claims
1. A company industry information analysis and identification system based on an AI large-scale model, characterized in that, It includes a preprocessing module for the company's industry information big data model, a company's industry information matching and acquisition module, a company's industry information caching module, and a CC code mapping and output sub-module; The preprocessing module for the company's industry information big data model includes company industry information acquisition and statistics; The company industry information matching and acquisition module includes uploading original company data, the company industry information big model preprocessing module matches company industry information according to the preprocessed data set, and the company industry information matching and acquisition module maintains and optimizes a dedicated prompt word template for interacting with the big model in the company industry information big model preprocessing module. The company industry information caching module will persistently store the original data of the matched companies. When the original data of the same company is matched again, the company's industry information can be obtained without going through the company industry information big model preprocessing module. The CC code mapping and output submodule receives the text analysis results returned by the large model, accurately maps them to a preset, structured industry classification system, and outputs them in a formatted manner.
2. The company industry information analysis and identification system based on AI large model according to claim 1, characterized in that, The prompt word template guides the company's industry information big data model preprocessing module to make industry judgments based on the company name and the industry knowledge base.
3. The company industry information analysis and identification system based on AI large model according to claim 1, characterized in that, The execution logic of the system is as follows: S1, upload the company information that needs to be analyzed and identified; S2, determine whether the original company data that has already been matched in the company industry information cache module has been hit; S3, if data is hit in S2, the data in the cache is directly extracted and the recognition ends; S4. If no data is found in S2, the identification is completed by accessing the large model in the large model preprocessing module of the company industry information and obtaining the company industry information through the existing large model data.
4. The company industry information analysis and identification system based on AI large model according to claim 1, characterized in that, The large models in the preprocessing module of the company's industry information large model are GPT, Wenxin Yiyan, and Tongyi Qianwen.