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Finding interesting patterns is a challenging task in data mining. Constraintbased mining is a well-known approach to this, and one for which constraintprogramming has been shown to be a well-suited and generic framework. Dominanceprogramming has been proposed as an extension that can capture an even widerclass of constraint-based mining problems, by allowing to compare relationsbetween patterns. In this paper, in addition to specifying a dominancerelation, we introduce the ability to specify an incomparability condition.Using these two concepts we devise a generic framework that can do a batch-wisesearch that avoids checking incomparable solutions. We extend the ESSENCElanguage and underlying modelling pipeline to support this. We use generatoritemset mining problem as a test case and give a declarative specification forthat. We also present preliminary experimental results on this specific problemclass with a CP solver backend to show that using the incomparability conditionduring search can improve the efficiency of dominance programming and reducesthe need for post-processing to filter dominated solutions.

Towards Improving Solution Dominance with Incomparability Conditions: A case-study using Generator Itemset Mining