Knowledge-based Sequence Mining with ASP - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Knowledge-based Sequence Mining with ASP

Résumé

We introduce a framework for knowledge-based sequence mining, based on Answer Set Programming (ASP). We begin by modeling the basic task and refine it in the sequel in several ways. First, we show how easily condensed patterns can be extracted by modular extensions of the basic approach. Second, we illustrate how ASP's preference handling capacities can be exploited for mining patterns of interest. In doing so, we demonstrate the ease of incorporating knowledge into the ASP-based mining process. To assess the trade-off in effectiveness, we provide an empirical study comparing our approach with a related sequence mining mechanism.
Fichier principal
Vignette du fichier
Gebser_IJCAI2016.pdf (392.76 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01327363 , version 1 (06-06-2016)

Identifiants

  • HAL Id : hal-01327363 , version 1

Citer

Martin Gebser, Thomas Guyet, René Quiniou, Javier Romero, Torsten Schaub. Knowledge-based Sequence Mining with ASP. IJCAI 2016- 25th International joint conference on artificial intelligence, Jul 2016, New-york, United States. pp.8. ⟨hal-01327363⟩
438 Consultations
463 Téléchargements

Partager

Gmail Facebook X LinkedIn More