2008 CommunityEvolutioninDynamicMult

• (Tang et al., 2008) ⇒ Lei Tang, Huan Liu, Jianping Zhang, and Zohreh Nazeri. (2008). “Community Evolution in Dynamic Multi-mode Networks.” In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2008). doi:10.1145/1401890.1401972

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• http://scholar.google.com/scholar?q=%22Community+evolution+in+dynamic+multi-mode+networks%22+2008
• http://portal.acm.org/citation.cfm?doid=1401890.1401972&preflayout=flat#citedby

Quotes

Abstract

A multi-mode network typically consists of multiple heterogeneous social actors among which various types of interactions could occur. Identifying communities in a multi-mode network can help understand the structural properties of the network, address the data shortage and unbalanced problems, and assist tasks like targeted marketing and finding influential actors within or between groups. In general, a network and the membership of groups often evolve gradually. In a dynamic multi-mode network, both actor membership and interactions can evolve, which poses a challenging problem of identifying community evolution. In this work, we try to address this issue by employing the temporal information to analyze a multi-mode network. A spectral framework and its scalability issue are carefully studied. Experiments on both synthetic data and real-world large scale networks demonstrate the efficacy of our algorithm and suggest its generality in solving problems with complex relationships.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 CommunityEvolutioninDynamicMult	Huan Liu Lei Tang Jianping Zhang Zohreh Nazeri			Community Evolution in Dynamic Multi-mode Networks				10.1145/1401890.1401972