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PREFIX-PROJECTION Global Constraint for Sequential Pattern Mining

Amina Kemmar 1 Samir Loudni 2 Yahia Lebbah 1 Patrice Boizumault 3 Thierry Charnois 2
2 Equipe CODAG - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
3 codag
Mines Nantes - Mines Nantes
Abstract : Sequential pattern mining under constraints is a challenging data mining task. Many efficient ad hoc methods have been developed for mining sequential patterns, but they are all suffering from a lack of genericity. Recent works have investigated Constraint Programming (CP) methods, but they are not still effective because of their encoding. In this paper, we propose a global constraint based on the projected databases principle which remedies to this drawback. Experiments show that our approach clearly outperforms CP approaches and competes well with ad hoc methods on large datasets.
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Amina Kemmar, Samir Loudni, Yahia Lebbah, Patrice Boizumault, Thierry Charnois. PREFIX-PROJECTION Global Constraint for Sequential Pattern Mining. Principles and Practice of Constraint Programming - 21st International Conference, CP 2015, Sep 2015, Cork, Ireland. ⟨10.1007/978-3-319-23219-5_17⟩. ⟨hal-01628152⟩

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