  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.
