Abstract
Automated thesaurus construction by collecting relations between lexical items (synonyms, antonyms, etc) has a long tradition in natural language processing. This has been done by exploiting dictionary structures or distributional context regularities (coocurrence, syntactic associations, or translation equivalents), in order to define measures of lexical similarity or relatedness. Dyvik had proposed to use aligned multilingual corpora and defines similar terms as terms that often share their translations. We evaluate the usefulness of this similarity for the extraction of synonyms, compared to the more widespread distributional approach.
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Muller, P., Langlais, P. (2011). Comparing Distributional and Mirror Translation Similarities for Extracting Synonyms. In: Butz, C., Lingras, P. (eds) Advances in Artificial Intelligence. Canadian AI 2011. Lecture Notes in Computer Science(), vol 6657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21043-3_40
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DOI: https://doi.org/10.1007/978-3-642-21043-3_40
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