Academic Expert Search Method Using Importance and Quality of Papers

논문의 중요성 및 품질을 이용한 학술 전문가 검색 기법

  • 이서희 (충북대학교 빅데이터협동과정) ;
  • 박윤정 (충북대학교 빅데이터협동과정) ;
  • 한진수 (충북대학교 정보통신공학과) ;
  • 최도진 (충북대학교 정보통신공학과) ;
  • 임종태 (충북대학교 정보통신공학과) ;
  • 복경수 (충북대학교 정보통신공학과) ;
  • 유재수 (충북대학교 정보통신공학과)
  • Received : 2016.10.25
  • Accepted : 2016.11.09
  • Published : 2016.12.28


An expert search method using a large amount of academic data that can provide users with representative research results and advice is required. Since the existing expert search methods perform the expert search based on user profile or activity information, they have a problem that it is hard to discriminate the expert when we do not know the user profile or activity information. In this paper, we propose an academic expert search method using the importance and quality of a paper. The importance of a paper is computed by considering its scarcity and up-to-date topics. The quality of a paper is evaluated by considering the number of citations, IF of Journal, recency and author relations. To show the superiority of the proposed method, we compare it with the existing scheme through the performance evaluation in terms of recall and precision.


Supported by : 한국연구재단, 정보통신기술진흥센터


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