A Mobile Context-Aware Proactive Recommendation Approach

Imen Akermi (1, 2) , Rim Faiz (2)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 LARODEC - Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus

The Proactive Context Aware Recommender Systems aim at combining a set of technologies and knowledge about the user context not only in order to deliver the most appropriate information to the user need at the right time but also to recommend it without a user query. In this paper, we propose a contextualized proactive multi-domain recommendation approach for mobile devices. Its objective is to efficiently recommend relevant items that match users’ personal interests at the right time without waiting for users to initiate any interaction. Our contribution is divided into two main areas: The modeling of a situational user profile and the definition of an aggregation frame for contextual dimensions combination.

Mots clés: Context modeling; Context-aware recommendation; User modeling; Proactive recommendation

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Imen Akermi, Rim Faiz. A Mobile Context-Aware Proactive Recommendation Approach. 7th International Conference on Computational Collective Intelligence (ICCCI 2015), Sep 2015, Madrid, Spain. pp.400-409. ⟨hal-01914028⟩