Reseach Interests 

Information retrieval - language model, semantic model, knowledge bases, conceptual indexing, passage retrieval
Natural language processing - concept detection 

Activitées 

Team - DRIM of the LIRIS laboratory from Lyon

Evaluation campaign - Participant of CLEF 2006-2007-2008 - Participant of french campaign Deft 2005-2006

Projects - IPRI (Internet, pluralisme and information redondancy), MIRO (Ondology driven information retrieval)

Ph. D

Vocabulary supports for precision oriented information retrieval systems: application to graphs for medical information retrieval.

Ph.d Computer science of University Joseph Fourier (since  2008/5/6) (funded by French ministry of research) LaboratoryLIG (MRIM Team)

Details -In my Ph.D. I explored a framework for the development of precision-oriented information retrieval models. This framework promotes the notion of vocabulary support to model expressive representations used by information retrieval systems. Indeed few modelling framework are available to specify information retrieval systems and we propose such a framework which focuses on the modelling of expressiveness. This framework can be used to choose the expressiveness of a model and to compare models on their level of expressiveness. In this framework we are moving towards the use of an expressive representation of the text. For this, we propose two models that are using representations with strong expressiveness. Both models are based on graphs representations. Through these two models are similar on their expressiveness, they are opposed on their underlying models. Indeed, we implement our first model with a model derived from conceptual graphs, and the second one with a model derived from the language modelling approach to information retrieval. To use these models on text, we propose the use of a two-step process based on language processing that promotes information coverage. The first step produces an intermediate representation of documents in which each sentence is represented by a graph. This step is domain dependent. The second step creates documents final representations from the intermediate one. We finally apply our two models on the medical domain. To do so, we use the meta-thesaurus UMLS and we propose several ways to build the intermediate representation of documents. The effectiveness of our model is proven by a number of experiments on the CLEF medical campaign. This campaign enables us to test our models in a real framework and to compare it to other teams. Indeed while taking part in this campaign in 2007 one of our models got the best results.

          

Supervisors - Jean-Pierre Chevalet (MRIM), Catherine Berrut (MRIM)