An ontology-based approach for detecting knowledge intensive tasks - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Digital Information Management Année : 2011

An ontology-based approach for detecting knowledge intensive tasks

Résumé

In the context detection field, an important challenge is automatically detecting the user's task, for providing contextualized and personalized user support. Several approaches have been proposed to perform task classification, all advocating the window title as the best discriminative feature. In this paper we present a new ontology-based task detection approach, and evaluate it against previous work. We show that knowledge intensive tasks cannot be accurately classified using only the window title. We argue that our approach allows classifying such tasks better, by providing feature combinations that can adapt to the domain and the degree of freedom in task execution.
Fichier principal
Vignette du fichier
rath-11-jdim.pdf (826.36 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00872209 , version 2 (11-10-2013)
hal-00872209 , version 1 (07-12-2021)

Identifiants

  • HAL Id : hal-00872209 , version 2

Citer

Andreas S. Rath, Didier Devaurs, Stefanie N. Lindstaedt. An ontology-based approach for detecting knowledge intensive tasks. Journal of Digital Information Management, 2011, 9 (1), pp.9-18. ⟨hal-00872209v2⟩
116 Consultations
257 Téléchargements

Partager

Gmail Facebook X LinkedIn More