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Patent Keyword Analysis using Gamma Regression Model and Visualization

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2022, 27(8), pp.143-149
  • DOI : 10.9708/jksci.2022.27.08.143
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : July 8, 2022
  • Accepted : August 17, 2022
  • Published : August 31, 2022

Sung-Hae Jun 1

1청주대학교

Accredited

ABSTRACT

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

Citation status

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