2009 RankingbasedClusteringofHeterog

• (Sun et al., 2009) ⇒ Yizhou Sun, Yintao Yu, and Jiawei Han. (2009). “Ranking-based Clustering of Heterogeneous Information Networks with Star Network Schema.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557107

Subject Headings:

Notes

• Categories and Subject Descriptors: H.2.8 Information Systems Applications: Database Applications — Data Mining.
• General Terms: Algorithms

Cited By

• http://scholar.google.com/scholar?q=%22Ranking-based+clustering+of+heterogeneous+information+networks+with+star+network+schema%22+2009
• http://portal.acm.org/citation.cfm?doid=1557019.1557107&preflayout=flat#citedby

Quotes

Author Keywords

Heterogeneous Information Network, Clustering

Abstract

A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden structures of the network and the individual role played by every object in each cluster. However, although clustering on homogeneous networks has been studied over decades, clustering on heterogeneous networks has not been addressed until recently.

A recent study proposed a new algorithm, RankClus, for clustering on bi-typed heterogeneous networks. However, a real-world network may consist of more than two types, and the interactions among multi-typed objects play a key role at disclosing the rich semantics that a network carries. In this paper, we study clustering of multi-typed heterogeneous networks with a star network schema and propose a novel algorithm, NetClus, that utilizes links across multi-typed objects to generate high-quality net-clusters. An iterative enhancement method is developed that leads to effective ranking-based clustering in such heterogeneous networks. Our experiments on DBLP data show that NetClus generates more accurate clustering results than the baseline topic model algorithm PLSA and the recently proposed algorithm, RankClus. Further, NetClus generates informative clusters, presenting good ranking and cluster membership information for each attribute object in each net-cluster.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2009 RankingbasedClusteringofHeterog	Yizhou Sun Yintao Yu Jiawei Han			Ranking-based Clustering of Heterogeneous Information Networks with Star Network Schema		KDD-2009 Proceedings	http://www.cs.uiuc.edu/~hanj/pdf/kdd09 ysun.pdf	10.1145/1557019.1557107		2009