Community prediction in citation networks = 인용 네트워크에서의 커뮤니티 예측

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Citation networks contain timely information about what researchers are interested in at a certain time. A community in such a network is built around either a renowned researcher or a common research field; either way, predicting how the community will change in the future will give insight into the research trend in the future. The paper proposes and analyzes methods to predict how communities change over time in the citation network graph without additional external information and based on link prediction and community detection. Different combinations of the proposed methods are also analyzed. Experiments show that the proposed methods can predict the citation community changes multiple timeframes in the future. Furthermore, the performance of the methods differs based on the prediction time span.
Advisors
Aviv Segevresearcher세게브Yoon, Wan-Chul윤완철
Description
한국과학기술원 : 지식서비스공학과,
Publisher
한국과학기술원
Issue Date
2012
Identifier
509494/325007  / 020104420
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 지식서비스공학과, 2012.8, [ vi, 52 p. ]

Keywords

Prediction; Community; Topic detection; Link prediction; Community Detection; 커뮤니티; 예측; 토픽 검출; 링크 예측; 인용 네트워크; 커뮤니티 검색; Citation Network

URI
http://hdl.handle.net/10203/181535
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=509494&flag=dissertation
Appears in Collection
IE-Theses_Master(석사논문)
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