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论文类型： 期刊论文

发表时间： 2012-11-01

发表刊物： Advances in Information Sciences and Service Sciences

收录刊物： EI、Scopus

卷号： 4

期号： 20

页面范围： 649-657

ISSN号： 19763700

摘要： In this paper, we study the problem of identifying communities given a seed set. At first, we modify the Approximate Personalized PageRank (APPR) algorithm to find a community with small conductance while examining only a small number of vertices. Secondly, we apply the modified APPR algorithm repeatedly with different approximation ratios to compute multiple communities as candidate communities, and select the one with smallest conductance as a result community. We also utilize network community profile (NCP) for adjusting the parameters of our modified APPR algorithm and quantifying statistical properties of result communities in a global view. Both theoretical and experimental results show the efficiency of the proposed algorithm and the quality of the output.