Towards a Recommender System from Semantic Traces for Decision Aid

Ning Wang (1) , Marie-Hélène Abel (1) , Jean-Paul Barthès (1) , Elsa Negre (2)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
2 LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision

Collaboration allows integrating intellectual resources and knowledge from all participants in order to achieve individual or collective goals. With the help of informational environments, we can better organize, realize and record collaboration. During interactions among users in such environments, each activity produces a set of traces. Such traces are recorded and classified, based on a model of traces and can be exploited to improve collaboration. In this article, we propose a semantic model of traces and analyze classified traces by means of TF-IDF. We exploit the results to offer users recommendations and decision aid.

Mots clés: Recommender System; Semantic Modelling; Traces of Interaction

Domaines: Réseaux sociaux et d'information [cs.SI]

Ning Wang, Marie-Hélène Abel, Jean-Paul Barthès, Elsa Negre. Towards a Recommender System from Semantic Traces for Decision Aid. 6th International conference on Knowledge Management and Information Sharing, Oct 2014, Rome, Italy. pp.274-279, ⟨10.5220/0005133502740279⟩. ⟨hal-01130026⟩