Jintao Tang
ABSTRACT
Applying graph clustering algorithms in real world networks needs to overcome two main challenges: the lack of prior knowledge and the scalability issue. This paper proposes a novel method based on the topological features of complex networks to optimize the clustering algorithms in real-world networks. More specifically, the features are used for parameter estimation and performance optimization. The proposed method is evaluated on real-world networks extracted from the web. Experimental results show improvement both in terms of Adjusted Rand index values as well as runtime efficiency.
- S. Milgram. The small world problem. 1967. Psychol Today 2, 60--67.Google Scholar
- D. J. Watts and S. H. Strogatz. 1998. Collective dynamics of 'small-world' networks. Nature 393, 440--442.Google ScholarCross Ref
- A-L. Barabási, R. Albert. 1999.Emergence of scaling in random networks. Science 286, 509--512.Google ScholarCross Ref
- Leonard Kaufman and Peter J. Rousseeuw. 1990. Finding groups in data: an introduction to cluster analysis. WILEY SER PROB STAT. Wiley.Google Scholar
- M. Girvan and M. E. J. Newman. 2002. Community structure in social and biological networks.PNAS 99 (12), 7821--7826.Google Scholar
- Jintao Tang,Ting Wang, Ji Wang, and Dengping Wei. 2009. Efficient social network approximate analysis on blogosphere based on network structure characteristics. In Proc. SNA-KDD 09. Google ScholarDigital Library
- M. E. J. Newmanand M. Girvan. 2004. Finding and evaluating community structure in networks. PHYS REV E 69 (2), 026113.Google ScholarCross Ref
- A. McCallum, K. Nigam, J. Rennie, and K.Seymore. 1999. A Machine Learning Approach to Building Domain-Specific Search Engines. In Proc.IJCAI '99. 662--667. Google ScholarDigital Library
Index Terms
- Using complex network features for fast clustering in the web
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