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In folksonomies, users use to share objects (movies, books, bookmarks, etc.)by annotating them with a set of tags of their own choice. With the rise of theWeb 2.0 age, users become the core of the system since they are both thecontributors and the creators of the information. Yet, each user has its ownprofile and its own ideas making thereby the strength as well as the weaknessof folksonomies. Indeed, it would be helpful to take account of users' profilewhen suggesting a list of tags and resources or even a list of friends, inorder to make a personal recommandation, instead of suggesting the more usedtags and resources in the folksonomy. In this paper, we consider users' profileas a new dimension of a folksonomy classically composed of three dimensions<users, tags, ressources> and we propose an approach to group users withequivalent profiles and equivalent interests as quadratic concepts. Then, weuse such structures to propose our personalized recommendation system of users,tags and resources according to each user's profile. Carried out experiments ontwo real-world datasets, i.e., MovieLens and BookCrossing highlight encouragingresults in terms of precision as well as a good social evaluation.

Nouvelle approche de recommandation personnalisee dans les folksonomies basee sur le profil des utilisateurs