Integration of association rules and ontologies for semantic query expansion

Authors:
Min Song;Il-Yeol Song;Xiaohua Hu;Robert B. Allen
Affiliations:
Department of Information Systems, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA;College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA;College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA;College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA
Venue:
Data & Knowledge Engineering
Year:
2007

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Abstract

We propose a novel semantic query expansion technique that combines association rules with ontologies and Natural Language Processing techniques. Our technique is different from others in that (1) it utilizes the explicit semantics as well as other linguistic properties of unstructured text corpus, (2) it makes use of contextual properties of important terms discovered by association rules, and (3) ontology entries are added to the query by disambiguating word senses. Using TREC ad hoc queries we achieve from 13.41% to 32.39% improvement for P@20 and from 8.39% to 14.22% for the F-measure.