Man-machine collaborative auditing and optimizing method for AI (Artificial Intelligence) generated content in field of literature and blog

By using a multi-dimensional content evaluation model and authoritative database analysis, combined with knowledge graph source tracing and verification, we have achieved efficient and accurate review and optimization of AI-generated content in the cultural heritage field. This has solved the quality control problem in existing technologies and improved review efficiency and content quality.

CN121936784APending Publication Date: 2026-04-28SHANGHAI BROADMESSE INT CREATIVE CO LTD
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Patent Information

Application Number
CN202511950647.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-23
Publication Date
2026-04-28

AI Technical Summary

Technical Problem

There are challenges in quality control for AI-generated content in the cultural heritage field. Existing review methods lack multi-dimensional assessments such as historical accuracy and cultural context compliance. The human-machine collaboration mechanism is imperfect, resulting in inaccurate review and an inability to continuously optimize the process.

Method used

By employing a multi-dimensional content evaluation model combined with authoritative historical document databases and cultural heritage corpus analysis, authoritative knowledge graph source verification is triggered. Through dynamic allocation of human and machine tasks and weighted decision fusion, a feedback dataset is constructed to optimize the AI ​​generation model.

Benefits of technology

It enables comprehensive and accurate quality screening of cultural heritage content, avoids the one-sidedness of single-dimensional evaluation, improves review efficiency and content quality, ensures the authenticity and logical consistency of generated content, and supports personalized adaptation of customized content.

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Abstract

The invention discloses a man-machine collaborative auditing and optimizing method for AI (artificial intelligence) generated content oriented to the field of literature and blog. The man-machine collaborative auditing and optimizing method comprises the following steps: S1, content acquisition and personalized constraint preprocessing: acquiring literature and blog field related content generated by an AI model; if the content is customized by a specific object, inputting an exclusive digital resource library and a style guide of the corresponding object into an AI generation model as constraint conditions; s2, multi-dimensional automatic evaluation: calling a multi-dimensional content evaluation model to carry out automatic analysis on the content, and outputting a quality score vector containing a plurality of evaluation dimension scores; s3, man-machine task dynamic allocation and collaborative auditing: calculating the comprehensive confidence of the content based on the quality score vector, and dynamically allocating the low-confidence content to the matched artificial auditor according to the confidence and the professional portrait of the auditor; and an auditor can trigger traceability verification based on the authoritative literature and blog mapping knowledge domain during auditing. According to the method, the AI generation content in the literature and blog field can be better audited and optimized.
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