Text governance method and device, equipment and medium

By employing a dual-mechanism approach to collect and construct knowledge graphs, the problem of low accuracy in text governance is addressed. This approach enables intelligent processing of external rule files and precise updates of internal rules, adapting to multiple business scenarios and improving the efficiency and accuracy of text governance.

CN121880283APending Publication Date: 2026-04-17CHINA MERCHANTS FINANCE HLDG CO LTD
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Patent Information

Application Number
CN202512042297.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-31
Publication Date
2026-04-17

AI Technical Summary

Technical Problem

Existing technologies have low accuracy in text governance, cannot achieve precise matching, real-time response and cross-scenario adaptation, rely on manual operation which is prone to errors, are difficult to build knowledge graphs, and have a lag in response to external rule changes.

Method used

External rule files are collected in real time through a dual mechanism of scheduled tasks and event-triggered tasks. Files that do not conform to the category are filtered out and labeled with the level. A knowledge graph is constructed, the correlation coefficient between business tags and data summaries is calculated, and changes in external rules are monitored and internal rule files are updated accurately.

Benefits of technology

It enables efficient processing of external rule files and accurate matching of internal rules, improving the accuracy and response speed of text governance, adapting to multiple business scenarios, and reducing compliance risks.

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Abstract

The invention relates to the technical field of data processing, and discloses a text governance method and device, equipment and a medium, and the method comprises the steps: collecting a preset enterprise external rule file in real time through a preset double mechanism of a timing scheduling task and an event triggering task; screening out files which do not accord with a preset category, labeling the files according to level labels, and storing the files into an internal database to form an internal specification file; extracting an internal specification data abstract, calculating a correlation coefficient between each service line label and the abstract, and determining a service line corresponding to the internal specification; constructing a knowledge graph by taking the file, the abstract, the label and the level as nodes and taking the correlation coefficient as an edge; when external specification changes are monitored, change content is collected, corresponding internal specification target files are identified, service labels with correlation coefficients exceeding a threshold value are screened to form a set, and corresponding service line internal specifications are collected; and by taking the change external specification level as a level, updating the internal specification corresponding to the service label with the level lower than the level in the set according to the change content. The accuracy of text governance can be improved.
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