Extracting Triplets of Technology Patents for TRIZ
[Objective]This paper proposes a model for extracting patented technology triplets.It tries to improve the accuracy of personalization,fine-grained,multi-dimensional deep extraction,and semantic association.[Methods]We constructed an extraction method based on the WeakLabel-Bert-BiGRU-CRF model for four technical dimensions:problems,solutions,functions,and effects.We evaluated the model using indicators such as the macro average.[Results]We examined the new model with patents in graphene energy storage applications.Compared to the Bert-BiGRU-CRF model,the proposed method achieved a macro average of over 0.8 for triplet extraction and reduced the workload of data annotation.[Limitations]The proposed model requires domain experts and patent analysts in data annotation,and annotation quality affects application effectiveness.[Conclusions]The proposed model could effectively extract patent technology triplets,which has a broad application prospect in scientific literature knowledge mining.
万方数据
维普
