Towards improving solution dominance with incomparability conditions : a case-study using Generator Itemset Mining
Abstract
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.
Citation
Kocak , G , Akgün , Ö , Miguel , I & Guns , T 2019 , Towards improving solution dominance with incomparability conditions : a case-study using Generator Itemset Mining . in The 18th workshop on Constraint Modelling and Reformulation (ModRef 2019), Proceedings . 25th International Conference on Principles and Practice of Constraint Programming (CP 2019) , Stamford , Connecticut , United States , 30/09/19 . < https://arxiv.org/abs/1910.00505 > conference
Publication
The 18th workshop on Constraint Modelling and Reformulation (ModRef 2019), Proceedings
Type
Conference item
Description
Funding: EPSRC (EP/P015638/1).Collections
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