An improved patent similarity measurement based on entities and semantic relations

文献类型： 外文期刊

第一作者： An, Xin

作者： An, Xin;Li, Jinghong;Xu, Shuo;Chen, Liang;Sun, Wei

作者机构：

关键词： Patent similarity measurement; Semantic analysis; Entities and semantic relations

期刊名称：JOURNAL OF INFORMETRICS （ 影响因子：5.107； 五年影响因子：5.421 ）

ISSN： 1751-1577

年卷期： 2021 年 15 卷 2 期

页码：

收录情况： SCI

摘要： Patent similarity measurement, as one of the fundamental building blocks for patent analysis, is able to derive technical intelligence efficiently, but also can detect the risk of infringement and evaluate whether the invention meets the criteria of novelty and innovation. However, traditional approaches make implicitly several assumptions, such as bag of words in each component, semantic direction irrelevance and so on. In order to relax these assumptions, this study proposes an improved methodology on the basis of entities and semantic relations (functional and non-functional relations), which takes semantic direction of each sequence structure and the word order information of each component into consideration. Meanwhile, an algorithm for calculating the global importance of each sequence structure is put forward. Finally, to verify the effectiveness and performance of the improved semantic analysis, a case study is conducted on the thin film head subfield in the field of hard disk drive. Extensive experimental results show that our approach is significantly more accurate. (c) 2021 Elsevier Ltd. All rights reserved.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序