지도학습 기반의 차원축소 모델을 이용한 특허 빅데이터 예측에 관한 연구

A Study on prediction of patent big datausing supervised learning with dimension reduction model
  • 이주현
  • 이준석
  • 강지호
  • 박상성
  • 장동식
  • 외 2명

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

Patent Big DataPatent EmbeddingDimension ReductionPLSIP-R&D
제목
지도학습 기반의 차원축소 모델을 이용한 특허 빅데이터 예측에 관한 연구
제목 (타언어)
A Study on prediction of patent big datausing supervised learning with dimension reduction model
저자
이주현이준석강지호박상성장동식홍성욱김선영
발행일
2019
저널명
(사)디지털산업정보학회 논문지
15
4
페이지
41 ~ 49