Dépister efficacement de l'information dans une banque documentaire : L'exemple de MEDLINE

Based on a relatively large subset representing one third of the MEDLINE collection, this paper evaluates ten different IR models (probabilistic, language model and vector-space approaches) using three different stemmers. The impact that manually assigned descriptors (MeSH headings) have on retrieval effectiveness is also evaluated. Finally, we propose both a new general blind-query expansion and a domain-specific query expansion scheme and compare them with the classic Rocchio approach. MOTS-CLÉS : Recherche d’information ; évaluation ; modèle probabiliste ; modèle de langue ; expansion automatique de requêtes ; indexation manuelle.