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We introduce geometric pattern mining, the problem of finding recurring localstructure in discrete, geometric matrices. It differs from existing patternmining problems by identifying complex spatial relations between elements,resulting in arbitrarily shaped patterns. After we formalise this new type ofpattern mining, we propose an approach to selecting a set of patterns using theMinimum Description Length principle. We demonstrate the potential of ourapproach by introducing Vouw, a heuristic algorithm for mining exact geometricpatterns. We show that Vouw delivers high-quality results with a syntheticbenchmark.

Vouw: Geometric Pattern Mining using the MDL Principle