• DocumentCode
    3579704
  • Title

    Term Extraction Using Co-occurrence in Abstract and First Claim for Patent Analysis

  • Author

    Peng Qu ; Junsheng Zhang ; Yanqing He ; Wen Zeng ; Hongjiao Xu

  • Author_Institution
    Inst. for Sci. & Tech. Inf. of China (ISTIC), Beijing, China
  • fYear
    2014
  • Firstpage
    60
  • Lastpage
    63
  • Abstract
    Patent information analysis need to extract patent terms from a vast amount of patent records rapidly and accurately. This paper proposes a patent term extraction method using co-occurrence in abstract and first claim sections of patent records. The research is carried out in three steps. In experiment 1, our proposed method´s F1 is 34.8% and higher than that of KEA with 21.0%. This demonstrates the good performance of our proposed method from a standard point of view. In experiment 2, our proposed method selects only 10,866 qualified terms from 28,044 candidate strings, with the selection percentage of 38.75%. There are 96.8% of total patent claims that contain the candidate terms at the same time. This illustrates the advantage of the proposed method in both eliminating unqualified candidates and providing a good coverage of patent texts from an actual application perspective.
  • Keywords
    data mining; information analysis; patents; cooccurrence; first claim section; patent information analysis; patent record; patent term extraction; Abstracts; Batteries; Feature extraction; Information analysis; Mutual information; Patents; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Identification, Information and Knowledge in the Internet of Things (IIKI), 2014 International Conference on
  • Type

    conf

  • DOI
    10.1109/IIKI.2014.19
  • Filename
    7063998