A conceptual representation of documents and queries for information retrieval systems by using light ontologies

This article presents a vector space model approach to representing documents and queries, based on concepts instead of terms and using WordNet as a light ontology. Such representation reduces information overlap with respect to classic semantic expansion techniques. Experiments carried out on the MuchMore benchmark and on the TREC-7 and TREC-8 Ad-Hoc collections demonstrate the effectiveness of the proposed approach.

► The proposed approach considers the representation of documents by using concepts instead of terms.
► The overall document score is computed how much the concepts expressed in a query are contained in the document.
► A general overview of the approach is presented.
► The approach has been evaluated on a set of standard information retrieval collections.