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http://dx.doi.org/10.5392/JKCA.2016.16.12.458

Academic Expert Search Method Using Importance and Quality of Papers  

Lee, Seo-Hee (충북대학교 빅데이터협동과정)
Park, Yun-jeong (충북대학교 빅데이터협동과정)
Han, Jin-Su (충북대학교 정보통신공학과)
Choi, Do-Jin (충북대학교 정보통신공학과)
Lim, Jong-Tae (충북대학교 정보통신공학과)
Bok, Kyoung-Soo (충북대학교 정보통신공학과)
Yoo, Jaesoo (충북대학교 정보통신공학과)
Publication Information
The Journal of the Korea Contents Association / v.16, no.12, 2016 , pp. 458-467 More about this Journal
Abstract
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.
Keywords
Expert Search; Paper Quality; Paper Importance; Academic Information; Academic Search;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
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