Abstract
Semantic similarity plays an important role in a number of applications including information extraction, information retrieval, document clustering and ontology learning. Most work has concentrated on English and other European languages. However, for the Thai language, there has been no research about word semantic similarity. This paper presents an experiment and benchmark data sets investigating the application of a WordNet-based machine measure to Thai similarity. Because there is no functioning Thai WordNet we also investigate the use of English WordNet with machine translation of Thai words.
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Osathanunkul, K., O’Shea, J., Bandar, Z., Crockett, K. (2011). Semantic Similarity Measures for the Development of Thai Dialog System. In: O’Shea, J., Nguyen, N.T., Crockett, K., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2011. Lecture Notes in Computer Science(), vol 6682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22000-5_56
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DOI: https://doi.org/10.1007/978-3-642-22000-5_56
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