A method and system for evaluating the innovativeness of power grid technology project requirements

By employing a self-supervised learning and hybrid retrieval mechanism based on a dual-tower structure, the problems of cross-modal semantic bias and single feature in the demand assessment of power grid technology projects are solved. This enables more precise and interpretable multi-dimensional innovative assessments, improving the accuracy and traceability of the assessments.

CN122175400APending Publication Date: 2026-06-09INNOVATION & INNOVATION CENT OF STATE GRID ZHEJIANG ELECTRIC POWER CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
INNOVATION & INNOVATION CENT OF STATE GRID ZHEJIANG ELECTRIC POWER CO LTD
Filing Date
2026-02-10
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

Existing technologies for evaluating the innovativeness of power grid technology projects suffer from problems such as isolated single-modal information, cross-style semantic bias, single features, and insufficient interpretability, making it difficult to achieve accurate and comprehensive evaluation.

Method used

A self-supervised learning method with a dual-tower structure is adopted. By cross-modal semantic alignment of knowledge graph vector representation with text vectors of standardized documents and demand documents, and a hybrid retrieval mechanism combining knowledge graph subgraph matching and vector library similarity, a multi-dimensional innovative evaluation index is constructed. A hierarchical Bayesian model is used for supervised training to generate interpretable evaluation results.

Benefits of technology

It achieves accurate matching of cross-modal data, reduces the probability of false detection and false negative detection, provides a reference for structured association and semantic similarity, generates interpretable and innovative evaluation results, and meets the business needs of power grid technology project management.

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Abstract

This invention relates to the field of project management technology and discloses a method and system for evaluating the innovativeness of power grid technology project requirements. The method includes at least the following steps: constructing a semantic alignment model using a dual-tower structure and self-supervised learning, with the semantic alignment of knowledge graph vector representation and all text vectors as the objective; training a hierarchical Bayesian model under supervised instruction based on the aligned text vectors and using expert innovativeness scores from second standardized requirement document data as labels to obtain an innovativeness scoring model; calculating multiple innovativeness evaluation indicators based on the hybrid retrieval results obtained through the target text vectors; inputting all innovativeness evaluation indicators into the innovativeness scoring model for quantitative scoring; and generating an innovativeness evaluation result containing qualitative evaluation conclusions and a traceable chain of evidence based on the quantitative scoring results. This invention enables effective evaluation of the innovativeness of power grid technology project requirements.
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