Journal of the Korean Society for information Management (정보관리학회지)

Korean Society for Information Management (한국정보관리학회)
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A Study on Developing a Prediction Model of Patent Citation Counts

특허인용 예측모형 구축에 관한 연구

  • Received : 2010.11.15
  • Accepted : 2010.11.25
  • Published : 2010.12.30
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Abstract

The purpose of this study is to develop a prediction model of patent citation counts based on major factors which affect patent citation. To this end, we performed multiple regression analysis between the patent citation counts and five explanatory variables such as the number of pages, the number of claims, the reference-average-citation rate, the strength of bibliographic coupling, and the document similarity proved as having 5% or more standardized variances($r^2$) with patent citation counts, with a test dataset of U.S. patents in five subject fields. As a result, our prediction models showed 58.3% to 89.6% predictability depending on subject fields and revealed the document similarity has the highest impact on citation counts among the five predictive variables in all the subject fields. The result of comparison between the predicted citation counts and the actual ones confirmed the usefulness of the citation prediction models built for each subject field.

이 연구에서는 특허의 인용에 영향을 미치는 주요 변수들을 토대로 특허의 피인용횟수를 예측하기 위한 모형을 제시하였다. 이를 위해 미국특허를 대상으로 5개 주제분야에 걸쳐 특허의 피인용횟수와 일정 수준 이상의 상관관계, 즉 5% 이상의 설명력을 갖는 것으로 밝혀진 페이지 수, 청구항 수, 참고문헌 평균 피인용횟수, 서지결합도, 문헌간유사도 등 5개 변수들을 토대로 다중회귀분석을 실시하였다. 연구결과에 따르면, 제시된 5개 주제분야의 특허인용 예측모형의 설명력은 주제분야에 따라 58.3%~89.6%로 나타났으며, 예측변수로 사용된 5개의 독립변수 중 특허 피인용횟수에 가장 영향력이 높은 변수는 '문헌간 유사도'로 나타났다. 또한 이 연구에서 추정된 주제분야별 예측모형을 토대로 산출한 특허 피인용횟수에 대한 예측값과 실제값을 비교한 결과 이들 예측모형은 5개 주제분야에서 모두 적합한 것으로 나타났다.

Keywords

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