Dongsheng Zhai
ABSTRACT
Analyzing technical contradictions according to TRIZ theory can help us solve the innovative and inventive problems effectively. However, the existing analysis and extraction methods of technical contradiction mainly rely on manual rule formulation and make less use of the semantics information, which limits the improvement of the efficiency and accuracy of the extraction. Consequently, this paper proposed an extraction method based on patent semantic space mapping. It adopted the Doc2Vec model to construct the semantic space of the patent text and trained extraction model by using feature vectors covering rich semantic relationships, which could make us recognize the technical contradictions from patents better. This paper used patent data in the automobile field as a sample to perform experiments. The accuracy of the technical contradiction recognition was improved compared with the baseline model based on rule formulation.
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