Using wordnet relations and semantic classes in information retrieval tasks

Authors:
Javi Fernández;Rubén Izquierdo;José M. Gómez
Affiliations:
University of Alicante, Department of Software and Computing Systems, Alicante, Spain;University of Alicante, Department of Software and Computing Systems, Alicante, Spain;University of Alicante, Department of Software and Computing Systems, Alicante, Spain
Venue:
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Year:
2009

Citing 8
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Abstract

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.