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In this paper, the authors study a visual data mining problem: Given a set of discovered overlapping submatrices of interest, how can people order the rows and columns of the data matrix to best display these submatrices and their relationships? The authors find this problem can be converted to the hypergraph ordering problem, which generalizes the traditional minimal linear arrangement (or graph ordering) problem and then they are able to prove the NP-hardness of this problem. The authors propose a novel iterative algorithm which utilizes the existing graph ordering algorithm to solve the optimal visualization problem.
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