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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)
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)
The overload of the information available on the web, held with the diversity of the user information needs and the ambiguity of their queries have led the researchers to develop personalized search tools that return only documents that meet the user profile representing his main interests and needs. We present in this paper a personalized document ranking(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)
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)
General Web search engines characterized by "onesize fits all" provide the same results for the same keyword queries even though these latter are submitted by different users with different intentions. In mobile Web search, the expected results for some queries could vary depending upon the user'slocation. We believe that identifying user's geographic(More)