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지도학습 기반의 차원축소 모델을 이용한 특허 빅데이터 예측에 관한 연구A Study on prediction of patent big datausing supervised learning with dimension reduction model
- Other Titles
- A Study on prediction of patent big datausing supervised learning with dimension reduction model
- Issue Date
- 2019
- Publisher
- (사)디지털산업정보학회
- Keywords
- Patent Big Data; Patent Embedding; Dimension Reduction; PLS; IP-R& D
- Citation
- (사)디지털산업정보학회 논문지, v.15, no.4, pp.41 - 49
- Indexed
- KCI
- Journal Title
- (사)디지털산업정보학회 논문지
- Volume
- 15
- Number
- 4
- Start Page
- 41
- End Page
- 49
- ISSN
- 1738-6667
- Abstract
- 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.
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