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论文类型： 会议论文

发表时间： 2008-12-12

收录刊物： EI、Scopus

卷号： 1

页面范围： 690-693

摘要： With the growth of publishing scientific literature on the World Wide Web, there is a great demand for clustering online scientific literature by using the citation patterns. A scientific community in the citation graph represents related papers on a single topic. In this paper we improve the random walk graph clustering algorithm to find scientific communities by using correlation coefficient in the citation graph as the similarity metric. Our experiment results show that the approach performs better than the original random walk graph clustering method. © 2008 IEEE.