Sequence mining under multiple constraints

Nicolas Béchet (1) , Peggy Cellier (2) , Thierry Charnois (3) , Bruno Crémilleux (4)

1 EXPRESSION - Expressiveness in Human Centered Data/Media
2 LIS - Logical Information Systems
3 LIPN - Laboratoire d'Informatique de Paris-Nord
4 Equipe CODAG - Laboratoire GREYC - UMR6072

In this paper, we address the problem of mining sequential patterns under multiple constraints. Unlike classical algorithms , our approach handles various types of constraints which are not only numeric but also symbolic and syntactic. These multiple constraints enable us to express a large scope of knowledge to focus on interesting patterns. We illustrate our approach with the detection of gene–rare disease relationships from biomedical texts for the documentation of rare diseases.

Mots clés: Sequential data mining; constraint-based data mining; Pattern discovery; information extraction; natural language processing

Domaines: Base de données [cs.DB]

Nicolas Béchet, Peggy Cellier, Thierry Charnois, Bruno Crémilleux. Sequence mining under multiple constraints. 30th Int. Conf. Symposium On Applied Computing (SAC 2015), 2015, Salamanca, Spain. pp.908 - 914, ⟨10.1145/354756.354849⟩. ⟨hal-01627364⟩