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In this section, we propose OPOSSUM (Optimal Partitioning
of Sparse Similarities Using Metis), a similarity-based clustering technique
particularly tailored to market-basket data.
OPOSSUM differs from other graph-based clustering
techniques by application-driven balancing of clusters, non-metric
similarity measures, and visualization driven heuristics for finding
an appropriate .