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2020 , Vol. 64 >Issue 14: 104 - 111

DOI: https://doi.org/10.13266/j.issn.0252-3116.2020.14.011

Patent Term Extraction by Integrating Keyword Knowledge From Paper

  • Yu Yan ,
  • Chen Lei ,
  • Jiang Jinde ,
  • Zhao Naixuan
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  • 1 Information Service Department, Nanjing Tech University, Nanjing 210009;
    2 Computer Science Department, Southeast University Chengxian College, Nanjing 211816;
    3 School of Business, Nanjing Xiaozhuang University, Nanjing 211171

Received date: 2018-12-23

  Revised date: 2019-10-05

  Online published: 2020-07-20

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Abstract

[Purpose/significance] In order to make up for the shortcomings of the patent text collection itself to limit the effect of patent term extraction, this paper proposes to use the rich keyword knowledge to obtain effective features outside the patent text to improve the patent term extraction effect. [Method/process] According to the keyword knowledge of related papers, two kinds of characteristic, degree of domain relevance and degree of head & tail are proposed to measure the possibility that candidate terms become terminology, and these characteristics are incorporated into the traditional method of patent term extraction. [Result/conclusion] The experimental results show that the degree of domain relevance and the degree of head & tail of the candidate terms obtained by using the keyword information of the papers make the method of combining the keyword knowledge of the papers significantly higher than the accuracy of the traditional term extraction method.

Key words： patent term extraction; paper; keyword

Cite this article

Yu Yan , Chen Lei , Jiang Jinde , Zhao Naixuan . Patent Term Extraction by Integrating Keyword Knowledge From Paper[J]. Library and Information Service, 2020 , 64(14) : 104 -111 . DOI: 10.13266/j.issn.0252-3116.2020.14.011

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