This paper presents a vector space model approach to representing documents and queries, which considers concepts instead of terms and uses WordNet as a light ontology. This representation reduces information redundancy with respect to conventional 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.
Ontology-based document and query representation may improve the effectiveness of information retrieval / M. Dragoni, C. da Costa Pereira, A.G.B. Tettamanzi - In: STAIRS 2010 : proceedings of the fifth starting AI researchers' symposium / [a cura di] T. Agotnes. - Amsterdam : IOS press, 2010. - ISBN 9781607506751. - pp. 89-100 (( Intervento presentato al 5. convegno Starting AI Researchers' Symposium (STAIRS) tenutosi a Lisbon, Portugal nel 2010.
Ontology-based document and query representation may improve the effectiveness of information retrieval
M. DragoniPrimo
;C. da Costa PereiraSecondo
;A.G.B. TettamanziUltimo
2010
Abstract
This paper presents a vector space model approach to representing documents and queries, which considers concepts instead of terms and uses WordNet as a light ontology. This representation reduces information redundancy with respect to conventional 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.
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
