  Finding interesting patterns is a challenging task in data mining. Constraint
based mining is a well-known approach to this, and one for which constraint
programming has been shown to be a well-suited and generic framework. Dominance
programming has been proposed as an extension that can capture an even wider
class of constraint-based mining problems, by allowing to compare relations
between patterns. In this paper, in addition to specifying a dominance
relation, we introduce the ability to specify an incomparability condition.
Using these two concepts we devise a generic framework that can do a batch-wise
search that avoids checking incomparable solutions. We extend the ESSENCE
language and underlying modelling pipeline to support this. We use generator
itemset mining problem as a test case and give a declarative specification for
that. We also present preliminary experimental results on this specific problem
class with a CP solver backend to show that using the incomparability condition
during search can improve the efficiency of dominance programming and reduces
the need for post-processing to filter dominated solutions.
