Content auditing method and device, equipment and medium

By segmenting and vectorizing documents and combining them with contextual information for dual verification, the problem of low efficiency and poor reliability in reviewing insurance terms on legal platforms has been solved, achieving more efficient and accurate content review.

CN122154695APending Publication Date: 2026-06-05PEOPLE'S INSURANCE COMPANY OF CHINA
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Patent Information

Application Number
CN202610042896.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-13
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing technologies are inefficient in the process of reviewing insurance terms on legal platforms and cannot guarantee the reliability of the review results.

Method used

The document to be reviewed is divided into paragraph blocks, vectorized, and then similarity is retrieved from the vector database. A second matching is performed by combining the context information of the text blocks to determine the target vector and calculate the semantic similarity of the paragraphs, and finally, the content is reviewed.

Benefits of technology

It improves the efficiency and accuracy of content review, reduces misjudgments caused by differences in expression, enhances the ability to distinguish semantically similar but context-unrelated content, and achieves more precise and granular document content review.

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Abstract

The invention provides a content auditing method and device, equipment and a medium, and the method comprises the steps: determining a first document type of a to-be-audited document, and carrying out the paragraph partitioning processing of the text content of the to-be-audited document according to the first document type, and obtaining a plurality of first text blocks; vectorizing the first text block to obtain a first vector, and determining a retrieval result of the first vector in a vector database, the retrieval result comprising at least one candidate vector and a similarity score of each candidate vector and the first vector; obtaining context information of the first vector in the to-be-audited document, and determining a content matching value between each candidate vector and the context information; determining a target vector from the plurality of candidate vectors according to the similarity score and the content matching value; determining paragraph semantic similarity according to the first vector and the target vector; and determining a content auditing result according to the paragraph semantic similarity corresponding to each first vector. Therefore, the content auditing efficiency and accuracy can be effectively improved.
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