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ICML
2006
IEEE

Spectral clustering for multi-type relational data

10 years 4 months ago
Spectral clustering for multi-type relational data
Clustering on multi-type relational data has attracted more and more attention in recent years due to its high impact on various important applications, such as Web mining, e-commerce and bioinformatics. However, the research on general multi-type relational data clustering is still limited and preliminary. The contribution of the paper is three-fold. First, we propose a general model, the collective factorization on related matrices, for multi-type relational data clustering. The model is applicable to relational data with various structures. Second, under this model, we derive a novel algorithm, the spectral relational clustering, to cluster multi-type interrelated data objects simultaneously. The algorithm iteratively embeds each type of data objects into low dimensional spaces and benefits from the interactions among the hidden structures of different types of data objects. Extensive experiments demonstrate the promise and effectiveness of the proposed algorithm. Third, we show th...
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2006
Where ICML
Authors Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip S. Yu
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