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HICSS
2008
IEEE

Clustering and the Biclique Partition Problem

11 years 8 months ago
Clustering and the Biclique Partition Problem
A technique for clustering data by common attribute values involves grouping rows and columns of a binary matrix to make the minimum number of submatrices all 1’s. As binary matrices can be viewed as adjacency matrices of bipartite graphs, the problem is equivalent to partitioning a bipartite graph into the smallest number of complete bipartite sub-graphs (commonly called “bicliques”). We show that the Biclique Partition Problem (BPP) does not have a polynomial time α-approximation algorithm, for any α ≥ 1, unless P=NP. We also show that the Biclique Partition Problem, restricted to whether at most k bicliques are sufficient (i.e. BPP(k)) for each positive integer k, has a polynomial time 2-approximation algorithm. In addition, we give an O(VE) time algorithm and BPP(2), and an O(V) algorithm to find an optimum biclique partition of trees.
Doina Bein, Linda Morales, Wolfgang W. Bein, C. O.
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where HICSS
Authors Doina Bein, Linda Morales, Wolfgang W. Bein, C. O. Shields Jr., Z. Meng, Ivan Hal Sudborough
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