Abstract
This work presents the concept-based text classification for organizing of traditional Thai medicine recipes. These recipes were translated from the Northeastern Thai palm leaf manuscripts. It is noted that each medicine recipe is presented with the ancient Isan language. The proposed method is called ‘concept-based text classification’, because we utilize ‘concepts’ as document features, where a concept is a surrogate of a word group having a same meaning. The main mechanisms in the method are the k-Nearest Neighbor algorithm and an ancient Isan dictionary, called Isan-Thai Markup Language (ITML). The objective of this work is to assign the Thai medicine recipes into predefined 5 groups. They are the groups of medicine recipe for headache and fever, stomachache and abdomen, skin, abscess, and faint and vertigo, respectively. After testing by recall, precision, and F-measure, it returns the satisfactory results of automatic text classification.
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Sibunruang, C., Polpinij, J. (2015). Concept-Based Text Classification of Thai Medicine Recipes Represented with Ancient Isan Language. In: Unger, H., Meesad, P., Boonkrong, S. (eds) Recent Advances in Information and Communication Technology 2015. Advances in Intelligent Systems and Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-19024-2_12
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DOI: https://doi.org/10.1007/978-3-319-19024-2_12
Publisher Name: Springer, Cham
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