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Ontology Based Query Expansion with a Probabilistic Retrieval Model

Bhogal, Jagdev and MacFarlane, A. (2013). Ontology Based Query Expansion with a Probabilistic Retrieval Model. In: Lupu, M., Kanoulas, E. and Loizides, F. (Eds.), Multidisciplinary Information Retrieval. Lecture Notes in Computer Science, 8201. (pp. 5-16). Berlin: Springer-Verlag. ISBN 9783642410567


This paper examines the use of ontologies for defining query context. The information retrieval system used is based on the probabilistic retrieval model. We extend the use of relevance feedback (RFB) and pseudo-relevance feedback (PF) query expansion techniques using information from a news domain ontology. The aim is to assess the impact of the ontology on the query expansion results with respect to recall and precision. We also tested the results for varying the relevance feedback parameters (number of terms or number of documents). The factors which influence the success of ontology based query expansion are outlined. Our findings show that ontology based query expansion has had mixed success. The use of the ontology has vastly increased the number of relevant documents retrieved, however, we conclude that for both types of query expansion, the PF results are better than the RFB results.

Publication Type: Book Section
Additional Information: The final publication is available at Springer via
Publisher Keywords: Ontology, Query Expansion, Probabilistic Retrieval Model, Okapi, relevance feedback, pseudo-relevance feedback
Subjects: Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science > Human Computer Interaction Design
Date Deposited: 22 Dec 2014 13:14
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