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A Model for Measuring the R&D Project Similarity using Patent Information

특허 정보를 활용한 R&D 과제 유사도 측정 모델

  • Kim, Jong-Bae (Graduate School of Software, Soongsil University) ;
  • Byun, Jung-Won (Department of Computer Science and Engineering, Soongsil University) ;
  • Sun, Dong-Ju (Patent Analysis Team, Korea Intellectual Property Strategy Institute) ;
  • Kim, Tae-Gyun (Patent Analysis Team, Korea Intellectual Property Strategy Institute) ;
  • Kim, Yung (Patent Analysis Team, Korea Intellectual Property Strategy Institute)
  • Received : 2014.03.03
  • Accepted : 2014.04.11
  • Published : 2014.05.31

Abstract

For efficient investments of government budgets, It is important to analyze the similarities of R&D projects. So, existing studies have proposed a techniques for analyzing similarities using keywords or segments. However, the techniques have low accuracy. We propose a technique for similarities of projects using patent information. To achieve our goal, we suggest three metrics that are based some mathematic theories; set theory and probability theory. In order to validate our technique, we perform case studies that have 156 R&D projects and 160,218 patent informations.

정부의 입장에서 R&D 과제간의 유사도를 분석하는 것은 불필요한 예산의 낭비를 없애고, R&D 투자의 효과를 높이는데 있어서 매우 중요한 문제이다. 그 동안, 문서의 내용을 대표하는 키워드를 중심으로 두 문서간의 유사도를 분석하거나, 문장 단위로 유사도를 분석함으로써, R&D 과제의 중복 여부를 판단하기 위한 연구들이 시도되어 왔으나, 여러 가지 이유로 아직까지 그 정확도는 매우 낮은 실정이다. 이에, 본 연구는 기 수행된 R&D 관련 특허를 조사, 수집하는 정부 R&D 특허기술동향조사사업의 특허분석 DB를 활용하여 R&D 과제간의 유사도를 분석할 수 있는 방안을 제시하고자 한다. 이를 위해, 집합 이론 및 확률 이론을 기반으로 한 유사도 측정 모델을 제시하였다. 또한, 제시한 모델의 검증을 위해 156개 과제, 160,218개의 유효특허를 기반으로 유효특허기반 과제 유사도 측정 실험을 수행하고, 그 사례를 제시하였다.

Keywords

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