Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering

Heterogeneous data co-clustering has attracted more and more attention in recent years due to its high impact on various applications. While the co-clustering algorithms for two types of heterogeneous data (denoted by pair-wise co-clustering), such as documents and terms, have been well studied in the literature, the work on more types of heterogeneous data (denoted by high-order co-clustering) is still very limited. As an attempt in this direction, in this paper, we worked on a specific case of high-order coclustering in which there is a central type of objects that connects the other types so as to form a star structure of the interships. Actually, this case could be a very good abstract for many real-world applications, such as the co-clustering of categories, documents and terms in text mining. In our philosophy, we treated such kind of problems as the fusion of multiple pairwise co-clustering sub-problems with the constraint of the star structure. Accordingly, we proposed the con...

• Type: Conference
• Year: 2005
• Where: KDD
• Authors: Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, Wei-Ying Ma
• Keywords: Consistent Bipartite Graph, Data Mining, General Terms Algorithms, Heterogeneous Data Co-clustering, KDD 2005