Computing Similarity of Patent Terms Based on Knowledge Graph
Li Jiaquan1(),Li Baoan2,You Xindong1,Lü Xueqiang1
1Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information cience & Technology University, Beijing 100101, China 2Computer School, Beijing Information Science & Technology University, Beijing 100101, China
[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.
李家全,李宝安,游新冬,吕学强. 基于专利知识图谱的专利术语相似度计算研究*[J]. 数据分析与知识发现, 2020, 4(10): 104-112.
Li Jiaquan,Li Baoan,You Xindong,Lü Xueqiang. Computing Similarity of Patent Terms Based on Knowledge Graph. Data Analysis and Knowledge Discovery, 2020, 4(10): 104-112.
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