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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
UBS - Université de Bretagne Sud, IRISA-D6 - MEDIA ET INTERACTIONS
2 LIS - Logical Information Systems
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
4 Equipe CODAG - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : 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.
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https://hal.archives-ouvertes.fr/hal-01627364
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Submitted on : Monday, November 6, 2017 - 7:31:06 PM
Last modification on : Tuesday, March 10, 2020 - 10:10:03 AM

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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⟩

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