Un système de recherche d'information personnalisée basé sur la modélisation multidimensionnelle de l'utilisateur. (Personalized Information retrieval system based on multidimensional user modeling)

The web explosion has led Information Retrieval (IR) to be extended and web search engines emergence. The conventional IR methods, usually intended for simple textual searches, faced new documents types and rich and scalable contents. The user, facing these evolutions, asks more for IR systems search results quality. In this context, the personalization main objective is improving results returned to the end user based sing on its perception and its interests and preferences. This thesis context is concerned with these di erent aspects. Its main objective is to propose new and e ective solutions to the personalization problem. To achieve this goal, a multidimensional user model based personalized search system is proposed. This system has two components : 1/ multidimensional user modeling /2 implicit users' collaboration through the construction of a users' models network. A system prototype was developed for the evaluation purpose that contains : information retrieval quality evaluation information retrieval quality evaluation with the spatial user model data information retrieval quality evaluation with the whole user model data and the users' models network. Experiments showed amelioration in the personalized search results compared to a baseline web search.