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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)
This paper deals with the use of ontologies for Information Retrieval. Roughly, the proposed approach consists in identifying important concepts in documents using two criterions, co-occurrence and semantic relatedness and then disambiguating them via an external general purpose ontology, namely WordNet. Matching the ontology and a document results in a set(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)