Abstract
This paper describes a new method to automatically obtain a new thesaurus which exploits previously collected information. Our method relies on different resources, such as a text collection, a set of source thesauri and other linguistic resources. We have applied different techniques in the different phases of the process. By applying indexing techniques, the text collection provides the set of initial terms of interest for the new thesaurus. Then, these terms are searched in the source thesauri, providing the initial structure of the new thesaurus. Finally, the new thesaurus is enriched by searching for new relationships among its terms. These relationships are first detected using similarity measures and then are characterized with a type (equivalence, hierarchy or associativity) by using different linguistic resources. We have based the system evaluation on the results obtained with and without the thesaurus in an information retrieval task proposed by the Cross-Language Evaluation Forum (CLEF). The results of these experiments have revealed a clear improvement of the performance.
Supported by project TIC2003-09481-C04.
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Pérez-Agüera, J.R., Araujo, L. (2006). Query Expansion with an Automatically Generated Thesaurus. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_93
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DOI: https://doi.org/10.1007/11875581_93
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