디지털산업정보학회논문지 (Journal of Korea Society of Digital Industry and Information Management)

  • 제15권4호
  • /
  • Pages.41-49
  • /
  • 2019
  • /
  • 1738-6667(pISSN)
  • /
  • 2713-9018(eISSN)
디지털산업정보학회 (Korea Society of Digital Industry and Information Management)
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DOI QR코드

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지도학습 기반의 차원축소 모델을 이용한 특허 빅데이터 예측에 관한 연구

A Study on prediction of patent big data using supervised learning with dimension reduction model

  • 이주현 (고려대학교 산업경영공학과) ;
  • 이준석 (엠아이큐브 솔루션) ;
  • 강지호 (고려대학교 산업경영공학과) ;
  • 박상성 (청주대학교 빅데이터 통계학과) ;
  • 장동식 (고려대학교 산업경영공학과) ;
  • 홍성욱 (주식회사 에스와이피 / 에스와이피 특허법률사무소) ;
  • 김선영 (주식회사 에스와이피 / 에스와이피 특허법률사무소)
  • 투고 : 2019.11.26
  • 심사 : 2019.12.06
  • 발행 : 2019.12.30
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초록

Patents are system to promote the development of industry by disclosing technology. The importance of recent patent is being emphasized. For this reason, companies apply for many patents. And they analyze the patent. Patent analysis helps to protect and foster their technology. Previously this method has been carried out by experts. Expert-based patent analysis, however, has the disadvantage of being time-consuming and expensive. Consequently, we try to solve this problems by developing prediction model. Therefore, this paper proposes a data-based patent analysis method using quantitative indicator and textual information. We confirmed the practical applicability of the proposed method through 1,831 autonomous vehicle patents. As a result, it was possible to confirmed that safety and lane detection related technologies are important.

키워드

참고문헌

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