基于专利知识图谱的专利术语相似度计算研究

Computing Similarity of Patent Terms Based on Knowledge Graph

【目的】利用专利知识图谱计算专利术语之间的相似度,从而计算专利文本之间的相似度以判断专利是否侵权。【方法】利用已构建的新能源汽车专利的知识图谱,结合术语的概念层次结构、术语在知识图谱中的距离、术语的语义相似度以及术语的属性计算术语之间的相似度。【结果】专利术语分类的准确率和召回率都在80%以上,相较于传统方法有明显提升。【局限】人工构建概念层次结构树以及标注术语的分类,可能会存在部分的分类错误。【结论】基于专利的知识图谱计算专利术语之间的相似度是可行的,使用分类的指标对方法进行评价时,指标的准确率达80%以上,对于后续的专利侵权检测研究具有很好的参考作用。

[Objective] The study uses patent knowledge graph to calculate similarities between patent terms,aiming to detect infringement cases from patent texts. [Methods] We calculated term similarities based on the knowledge graph of new energy vehicle patent. Other factors included: the concept hierarchy of terms, the distance between terms in the knowledge graph, the semantic similarity of terms, as well as the attributes of terms.[Results] The accuracy and recall rates of patent term classification were more than 80%, which were significantly higher than those of the traditional methods. [Limitations] Manual construction of concept hierarchy tree and annotation of term classification might yield errors. [Conclusions] It is feasible to compute similarities between patent terms based on the knowledge graph, which provides good reference for future research.