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Author:

Chen, Liang (Chen, Liang.) | Xu, Shuo (Xu, Shuo.) (Scholars:徐硕) | Shang, Weijiao (Shang, Weijiao.) | Wang, Zheng (Wang, Zheng.) | Wei, Chao (Wei, Chao.) | Xu, Haiyun (Xu, Haiyun.)

Indexed by:

EI

Abstract:

Information extraction is the fundamental technique for text-based patent analysis in era of big data. However, the specialty of patent text enables the performance of general information-extraction methods to reduce noticeably. To solve this problem, an in-depth exploration has to be done for clarify the particularity in patent information extraction, thus to point out the direction for further research. In this paper, we discuss the particularity of patent information extraction in three aspects: (1) what is the special about labeled patent dataset? (2) What is special about word embeddings in patent information extraction? (3) What kind of method is more suitable for patent information extraction? © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Keyword:

Digital libraries Patents and inventions Data mining Information retrieval

Author Community:

  • [ 1 ] [Chen, Liang]Institute of Scientific and Technical Information of China, Beijing, China
  • [ 2 ] [Xu, Shuo]College of Economics and Management, Beijing University of Technology, Beijing, China
  • [ 3 ] [Shang, Weijiao]Research Institute of Forestry Policy, Information Chinese Academy of Forestry, Beijing, China
  • [ 4 ] [Wang, Zheng]Institute of Scientific and Technical Information of China, Beijing, China
  • [ 5 ] [Wei, Chao]Institute of Scientific and Technical Information of China, Beijing, China
  • [ 6 ] [Xu, Haiyun]Chengdu Library and Information Center, Chinese Academy of Sciences, Beijing, China

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ISSN: 1613-0073

Year: 2020

Volume: 2658

Page: 63-72

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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