Recognition of Terms in Spanish by Applying a Contrastive Approach
Abstract
In this article we present a methodology for identifying and extracting terms from text sources in Spanish corresponding specialized-domain corpus by means of a contrastive approach. The contrastive approach requires a measure for assigning relevance to words occurring both in domain corpus and reference corpus. Therefore, in this work we explored four measures used for assigning relevance to words with the goal of incorporating the best measure in our methodology. Our results show a better performance of rank difference and relative frequency ratio measures compared with log-likelihood ratio and the measure used by Termostat.
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