Contextual Sequential Pattern Mining - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Accéder directement au contenu
Communication Dans Un Congrès Année : 2010

Contextual Sequential Pattern Mining

Résumé

Traditional sequential patterns do not take into account additional contextual information since patterns extracted from data are usually general. By considering the fact that a pattern is associated with one specific context the decision expert can then adapt his strategy considering the type of customers. In this paper we propose to mine more precise patterns of the form "young users buy products A and B then product C, while old users do not follow this same behavior". By highlighting relevant properties of such contexts, we show how contextual sequential patterns can be extracted by mining the database in a concise manner. We conduct our experimental evaluation on real-world data and demonstrate performance issues.
Fichier principal
Vignette du fichier
Rabatel_DDDM2010.pdf (355.24 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

lirmm-00670950 , version 1 (16-02-2012)

Identifiants

Citer

Julien Rabatel, Sandra Bringay, Pascal Poncelet. Contextual Sequential Pattern Mining. DDDM: Domain Driven Data Mining, Dec 2010, Sydney, NSW, Australia. pp.981-988, ⟨10.1109/ICDMW.2010.182⟩. ⟨lirmm-00670950⟩
110 Consultations
252 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More