Abstract

Abstract —This paper reports an experiment to evaluate a Cross Language Information Retrieval (CLIR) system that uses a multilingual ontology to improve query translation in the travel domain. The ontology-based approach significantly outperformed the Machine Readable Dictionary translation baseline using Mean Average Precision as a metric in a user-centered experiment. Index terms —Ontology, multilingual, cross language information retrieval. I. I NTRODUCTION HE growing requirement on the Internet for users to access information expressed in language other than their own has led to Cross Language Information Retrieval (CLIR) becoming established as a major topic in IR. One approach to CLIR uses different translation approaches to translate queries to documents and indexes in other languages. As queries submitted to search engines suffer lack of context, translation approaches have great problems with resolving query ambiguity. In our approach, we built a multilingual ontology to be used as a translation base for CLIR. In this paper we evaluate our proposed query translation methodology and compare it with a base line system that uses a Machine Readable Dictionary (MRD) as translation base in a user-centered experiment. II. B

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