Indian Journal of Science and Technology
Year: 2015, Volume: 8, Issue: Supplementary 1, Pages: 1-5
MuYeong, Kang1 , Jae-Do, Shin2 and Byungkyu Kim3*
1 Information Service Center, Korea Institute of Science and Technology Information, Daejeon, 305-806, South Korea
2 Department of Computer Engineering, ChungNam National University, Daejeon, 305-764, South Korea
3 Division of Policy Research, Korea Institute of Science and Technology Information, Daejeon, 305-806, South Korea; [email protected]
Journal subject classification is important in terms of being used for scholarly information service and foundation of disciplinary research analysis. Subject classification by subject matter experts or journal information takes a significant amount of time or does not provide accurate information about subject respectively. In order to overcome these current problems, this research suggested automatic subject classification method by using SCI journal information cited by domestic science and engineering journals, and it also investigated the classification results. We found that using the entire cited academic journals has a better accuracy rate than using the most cited three or five academic journals, and this research showed that the more academic journals included in the analysis the more accurate the rate. Especially, this research utilised the subject category of Web of Science as the standard of subject classification and provided foundations for comparing subject category structure in academic research results in KSCI and SCI.
Keywords: Automatic Subject Classification, Korean Journals, KSCI
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