Context Factors in Context-Aware Recommender System

Zahra Vahidi Ferdousi , Elsa Negre (1) , Dario Colazzo (2)

1 LIFAT - Laboratoire d'Informatique Fondamentale et Appliquée de Tours
2 LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision

With the rise in volume of data from various sources, we have an increasing need of recommender systems, which provide a data filtering to help users to find appropriate information. To satisfy even more users' needs, a new kind of recommender systems called context-aware recommender systems (CARS) integrate contextual information related to the user in their recommendation process. However there exists no unique definition for context. In this poster we propose a context representation for CARS, to improve upon previous propositions, which can be used for a large spectrum of applications.

Domaines: Réseaux sociaux et d'information [cs.SI]; Intelligence artificielle [cs.AI]

Zahra Vahidi Ferdousi, Elsa Negre, Dario Colazzo. Context Factors in Context-Aware Recommender System. AISR 2017 Atelier interdisciplinaire sur les systèmes de recommandation, May 2017, Paris, France. ⟨hal-01643553⟩