Hybrid expert multi-classification method and system combined with embedded double-model organizational structure

By combining the hybrid expert multi-classification method embedded in the dual-model organizational structure, using the hybrid expert mechanism and data distribution consistency optimization, a scientific value sentence recognition model and multi-classification model are constructed, and the problems of low efficiency and poor accuracy of scientific literature value sentence classification in the existing technology are solved, and efficient and accurate scientific value sentence classification is achieved.

CN119646224AActive Publication Date: 2025-03-18DOCUMENT & INFORMATION CENT OF CHINESE ACAD OF SCI
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Patent Information

Application Number
CN202411805132.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-10
Publication Date
2025-03-18
Estimated Expiration
2044-12-10

AI Technical Summary

Technical Problem

When processing scientific literature, the existing scientific literature value sentence classification methods have problems such as low processing efficiency and difficulty in ensuring accuracy.

Method used

By combining the hybrid expert multi-classification method embedded in the dual-model organizational structure, the hybrid expert mechanism and data distribution consistency optimization are adopted to construct a scientific value sentence recognition model and a multi-classification model to achieve efficient and accurate scientific value sentence classification.

Benefits of technology

It effectively improves the classification accuracy of scientific value sentences, realizes efficient and accurate analysis of multi-dimensional academic, application and innovation values, and solves the problems of low classification efficiency and poor accuracy in the existing technology.

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Abstract

The invention discloses a hybrid expert multi-classification method and system combined with an embedded double-model organization structure, is applied to the technical field of data processing, and constructs a scientific value sentence recognition model by performing deep learning on a pre-training model based on a data distribution consistency threshold and a scientific value sentence training corpus. Based on a hybrid expert mechanism, a scientific value sentence multi-classification model is built, and the scientific value sentence multi-classification model comprises an academic value expert sub-model, an application value expert sub-model, an innovation value expert sub-model and a gating network. And packaging the scientific value sentence recognition model and the scientific value sentence multi-classification model into a scientific value sentence detection double model to obtain scientific and technical literatures. And inputting the scientific and technical literature into the scientific value sentence detection double model to obtain a scientific value sentence comprehensive classification result. The technical problems that in the prior art, when an existing scientific literature value sentence classification method is used for processing scientific literatures, the processing efficiency is low, and the accuracy is difficult to guarantee are solved.
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