• DocumentCode
    1827256
  • Title

    A method for assessing patent similarity using direct and indirect citation links

  • Author

    Wu, Hsiao-Chun ; Chen, Hung-Yi ; Lee, Kung-Yen ; Liu, Ying-Chieh

  • Author_Institution
    Dept. of Bus. Adm., Chaoyang Univ. of Technol., Taichung, Taiwan
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    149
  • Lastpage
    152
  • Abstract
    Assessing patent similarity is a fundamental and critical step in patent citation analysis. When evaluating a similarity among two patents, considering both direct and indirect citation links leads to more precise similarity assessment. This study proposes a method for assessing patent compound similarity that includes direct and indirect similarities. Given a direct similarity matrix that represents a patent citation network, the method calculates indirect similarity matrices and then obtains a compound similarity matrix. Keyword analysis in the text mining is employed to obtain a similarity for a pair of patents. In addition, two criterion are proposed for validating the compound similarities for the patent citation network.
  • Keywords
    citation analysis; data mining; matrix algebra; patents; citation links; keyword analysis; patent citation analysis; patent similarity assessment; similarity matrix; text mining; Art; Citation analysis; Compounds; Couplings; Equations; Mathematical model; Patents; Citation link; keyword analysis; patent citation; patent similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference on
  • Conference_Location
    Macao
  • ISSN
    2157-3611
  • Print_ISBN
    978-1-4244-8501-7
  • Electronic_ISBN
    2157-3611
  • Type

    conf

  • DOI
    10.1109/IEEM.2010.5674439
  • Filename
    5674439