  Because of the increasing number of electronic data, designing efficient
tools to retrieve and exploit documents is a major challenge. Current search
engines suffer from two main drawbacks: there is limited interaction with the
list of retrieved documents and no explanation for their adequacy to the query.
Users may thus be confused by the selection and have no idea how to adapt their
query so that the results match their expectations. This paper describes a
request method and an environment based on aggregating models to assess the
relevance of documents annotated by concepts of ontology. The selection of
documents is then displayed in a semantic map to provide graphical indications
that make explicit to what extent they match the user's query; this man/machine
interface favors a more interactive exploration of data corpus.
