Advanced
A Study on Utilization of Korea Science Citation Database(KSCD) Based on Data Mining Techniques
A Study on Utilization of Korea Science Citation Database(KSCD) Based on Data Mining Techniques
Journal of Information Management. 2012. Oct, 43(4): 191-210
  • Published : October 30, 2012
Download
PDF
Export by style
Article
Author
Metrics
Cited by
About the Authors
Park, Jong-Hyun
Choi, Seon-Heui
Kim, Byung-Kyu

Abstract
Scholarly science citation data is typically of large volume and consists of a variety of data. Moreover, the volume of data is increasing more and more. Therefore, there are some requirements to store and manage the data efficiently and Korea Institute of Science and Technology Information (KISTI) develops Korea Science Citation Database (KSCD) which manage and serve very large-volume of korea science technique information including citation data. However, current services based on KSCD are not enough for various users. Thus, it is important issue to offer a variety of services using KSCD. For example, if a user searches articles described by a specific author, then a user may want to find not only the articles cited by a certain author but also those articles that study similar topics. However, it is not always easy to provide these services with citation data. Therefore, this paper surveys studies about services using citation data in order to find approaches for better utilizing KSCD. Especially, this paper considers data mining techniques, because data mining is one of the main techniques to extracting semantic information from big data. Therefore, this paper discusses methods for utilizing large volume of KSCD based on data mining technique.
Keywords
References