Resume data automatic labeling method, system, medium and equipment

By constructing a tagging system and a large language model for automatic annotation of historical data, the problem of ineffective utilization of equipment and component historical data in the power industry has been solved, and automatic structuring of historical data and continuous updating of fault knowledge have been achieved.

CN120930764APending Publication Date: 2025-11-11SUZHOU NUCLEAR POWER RES INST CO LTD +1
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Patent Information

Application Number
CN202511013194.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-22
Publication Date
2025-11-11

AI Technical Summary

Technical Problem

In the power industry, the history data of equipment components is not effectively stored and utilized, making it difficult to solidify and pass on expert experience, and hindering the automatic history analysis and extraction and utilization of fault knowledge.

Method used

A tagging system is constructed, which obtains resume data through a large language model and extracts fault knowledge. If a match is found, a new tag is added; if no match is found, a new tag is generated, thus realizing automatic labeling of resume data.

Benefits of technology

It has achieved automatic structuring and standardization of resume data, established a continuous update mechanism for the fault knowledge base, solved the data silo problem, and improved the efficiency of fault knowledge extraction and utilization.

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Abstract

The invention relates to a method, a system, a medium and equipment for automatically labeling resume data. The method comprises the following steps of: constructing a label system; obtaining new resume data, and performing fault knowledge extraction according to the tag system through the large language model to obtain extracted fault knowledge; judging whether the extracted fault knowledge is matched in a label library or not, and if yes, newly adding the extracted fault knowledge in the fault mode; and if not, generating a new tag through the large language model. According to the method, the label system of the resume is constructed, after the new resume data is generated, the resume data is automatically structured, the extracted label data is standardized through comparison of the knowledge base and is standardized in the resume, and new labels are automatically generated for labels which do not exist in the existing knowledge base; an effective fault knowledge base continuous updating mechanism is established, automatic analysis of resumes and fault knowledge extraction, accumulation and utilization are achieved, and the problems of data islands and the like are effectively solved.
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