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A Greedy Search Approach to Co-clustering Sparse Binary MatricesTools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on In Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on (2006), pp. 363-370.
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AbstractA co-clustering algorithm for large sparse binary data matrices, based on a greedy technique and enriched with a local search strategy to escape poor local maxima, is proposed. The algorithm starts with an initial random solution and searches for a locally optimal solution by successive transformations that improve a quality function which combines row and column means together with the size of the co-cluster. Experimental results on synthetic and real data sets show that the method is able to find significant co-clusters
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