Patent Keyphrase Extraction Based on Patent Term and Layer Information
Yu Yan1,2(),Wang Li1,Zheng Siyu1
1Institute of Information Management and Technology, Nanjing Tech University, Nanjing 210009, China 2College of Electronic and Computer Engineering, Southeast University Chengxian College, Nanjing 210088, China
[Objective] This paper proposes a patent key phrase extraction method incorporating terminology and hierarchical information to improve the accuracy of patent key phrase extraction. It tries to improve the existing graph-based model, which tends to select long key phrases and ignores the phrases’ positional information. [Methods] Based on the traditional graph model, we constructed a new terminology degree metric to measure the terminological information of candidate key phrases. Considering the characteristics of patent documents, we divided patents into several hierarchies and used their weight metrics to measure the positional information of candidate key phrases. [Results] By incorporating terminology information, the F value of the new method improved by 7.615% (nanotechnology), 11.515% (image recognition), 9.813% (chip), and 8.839% (LCD). By incorporating the hierarchical information, the new method’s F value improved by 9.880% (nanotechnology), 6.929% (image recognition), 6.099% (chip), and 5.576% (LCD). [Limitations] The candidate key phrase selection method based on part-of-speech rules may produce more noise. [Conclusions] The proposed method effectively enhances the accuracy of patent key phrase extraction.
俞琰, 王丽, 郑斯煜. 融入术语与层级信息的专利关键短语抽取方法研究[J]. 数据分析与知识发现, 2023, 7(6): 99-112.
Yu Yan, Wang Li, Zheng Siyu. Patent Keyphrase Extraction Based on Patent Term and Layer Information. Data Analysis and Knowledge Discovery, 2023, 7(6): 99-112.
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