Mining Contextual Preference Rules for Building User Profiles

Sandra de Amo , Mouhamadou Saliou Diallo (1, 2) , Cheikh T. Diop (2) , Arnaud Giacometti (1) , D. Li Haoyuan (1) , Arnaud Soulet (1)

1 BDTLN - Bases de données et traitement des langues naturelles
2 UGB - Université Gaston Berger de Saint-Louis Sénégal

The emerging of ubiquitous computing technologies in recent years has given rise to a new field of research consisting in incorporating context-aware preference querying facilities in database systems. One important step in this setting is the Preference Elicitation task which consists in providing the user ways to inform his/her choice on pairs of objects with a minimal effort. In this paper we propose an automatic preference elicitation method based on mining techniques. The method consists in extracting a user profile from a set of user preference samples. In our setting, a profile is specified by a set of contextual preference rules verifying properties of soundness and conciseness. We evaluate the efficacy of the proposed method in a series of experiments executed on a real-world database of user preferences about movies.

Domaines: Informatique et langage [cs.CL]

Sandra de Amo, Mouhamadou Saliou Diallo, Cheikh T. Diop, Arnaud Giacometti, D. Li Haoyuan, et al.. Mining Contextual Preference Rules for Building User Profiles. 14th International Conference on Data Warehousing and Knowledge Discovery, 2012, Vienne, Austria. pp.229-242. ⟨hal-01024358⟩