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In the context of biomedical information retrieval (IR), this paper explores the relationship between the document's global context and the query's local context in an attempt to overcome the term mis-match problem between the user query and documents in the collection. Most solutions to this problem have been focused on expanding the query by discovering(More)
Most of the previous approaches surrounding collaborative information retrieval (CIR) provide either a user-based mediation, in which the system only supports users' collaborative activities, or a system-based mediation, in which the system plays an active part in balancing user roles, re-ranking results, and distributing them to optimize overall retrieval(More)
Recent studies suggest that significant improvement in information retrieval performance can be achieved by combining multiple representations of an information need. The paper presents a genetic approach that combines the results from multiple query evaluations. The genetic algorithm aims to optimise the overall relevance estimate by exploring different(More)
This paper presents a novel retrieval approach for literature access based on social network analysis. In fact, we investigate a social model where authors represent the main entities and relationships are extracted from co-author and citation links. Moreover, we define a weighting model for social relationships which takes into account the authors(More)
Most Web search engines use the content of the Web documents and their link structures to assess the relevance of the document to the user’s query. With the growth of the information available on the web, it becomes difficult for such Web search engines to satisfy the user information need expressed by few keywords. First, personalized information retrieval(More)
In the context of document retrieval in the biomedical domain, this paper introduces a novel approach to searching for biomedical information using contextual semantic information. More specifically, we propose to combine the contextual semantic information in documents and user queries in an attempt to improve the performance of biomedical information(More)
A key challenge in information retrieval is the use of contex-tual evidence within the ad-hoc retrieval. Our contribution is particularly based on the belief that contextual retrieval is a decision making problem. For this reason we propose to apply influence diagrams which are extension of Bayesian networks to such problems, in order to solve the hard(More)
RÉSUMÉ. La personnalisation d'un processus d'accès à l'information a pour objectif de déli-vrer à l'utilisateur une information appropriée à ses préférences, ses centres d'intérêts ou plus globalement son profil. Ce papier présente une technique de construction du profil de l'uti-lisateur qui s'inscrit dans une approche statistique utilisant le comportement(More)
Collaborative information retrieval systems often rely on division of labor policies. Such policies allow work to be divided among collaborators with the aim of preventing redundancy and optimizing the synergic effects of collaboration. Most of the underlying methods achieve these goals by the means of explicit vs. implicit role-based mediation. In this(More)
Within the information overload on the web and the diversity of the user interests, it is increasingly difficult for search engines to satisfy the user information needs. Personalized search tackles this problem by considering the user profile during the search. This paper describes a personalized search approach involving a semantic graph-based user(More)