Patent Registration Prediction Methodology Using Multivariate Statistics

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著者

    • JUNG Won-Gyo
    • Division of Information Management Engineering, Korea University
    • PARK Sang-Sung
    • Division of Information Management Engineering, Korea University
    • JANG Dong-Sik
    • Division of Information Management Engineering, Korea University

抄録

Whether a patent is registered or not is usually based on the subjective judgment of the patent examiners. However, the patent examiners may determine whether the patent is registered or not according to their personal knowledge, backgrounds etc. In this paper, we propose a novel patent registration method based on patent data. The method estimates whether a patent is registered or not by utilizing the objective past history of patent data instead of existing methods of subjective judgments. The proposed method constructs an estimation model by applying multivariate statistics algorithm. In the prediction model, the application date, activity index, IPC code and similarity of registration refusal are set to the input values, and patent registration and rejection are set to the output values. We believe that our method will contribute to improved reliability of patent registration in that it achieves highly reliable estimation results through the past history of patent data, contrary to most previous methods of subjective judgments by patent agents.

収録刊行物

  • IEICE transactions on information and systems

    IEICE transactions on information and systems 94(11), 2219-2226, 2011-11-01

    The Institute of Electronics, Information and Communication Engineers

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各種コード

  • NII論文ID(NAID)
    10030194057
  • NII書誌ID(NCID)
    AA10826272
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    09168532
  • データ提供元
    CJP書誌  J-STAGE 
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