A global Constraint for mining Sequential Patterns with GAP constraint
Abstract
Sequential pattern mining (SPM) under gap constraint is a challenging task. Many efficient specialized methods have been developed but they are all suffering from a lack of genericity. The Constraint Programming (CP) approaches are not so effective because of the size of their encodings. In[7], we have proposed the global constraint Prefix-Projection for SPM which remedies to this drawback. However, this global constraint cannot be directly extended to support gap constraint. In this paper, we propose the global constraint GAP-SEQ enabling to handle SPM with or without gap constraint. GAP-SEQ relies on the principle of right pattern extensions. Experiments show that our approach clearly outperforms both CP approaches and the state-of-the-art cSpade method on large datasets.
Cite
@article{arxiv.1511.08350,
title = {A global Constraint for mining Sequential Patterns with GAP constraint},
author = {Amina Kemmar and Samir Loudni and Yahia Lebbah and Patrice Boizumault and Thierry Charnois},
journal= {arXiv preprint arXiv:1511.08350},
year = {2015}
}