Abstract
Morphology is the process of analyzing the internal structure of words. Grammatical features and properties are used for this analysis. Like other Dravidian languages, Tamil is a highly agglutinative language with a rich morphology. Most of the current morphological analyzers for Tamil mainly use segmentation to deconstruct the word to generate all possible candidates and then either grammar rules or tagging mismatch is used during post processing to get the best candidate. This paper presents a morphological engine for Tamil that uses grammar rules and an annotated corpus to get all possible candidates. A support vector machines classifier is employed to determine the most probable morphological deconstruction for a given word. Lexical labels, respective frequency scores, average length and suffixes are used as features. The accuracy of our system is 98.73 % and a F-measure of .943, which is more than the same reported by other similar research.
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, Revised edn, pp. 93–260. Poobalasingam Publications, Sri Lanka (2010)
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Mokanarangan, T. et al. (2016). Tamil Morphological Analyzer Using Support Vector Machines. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science(), vol 9612. Springer, Cham. https://doi.org/10.1007/978-3-319-41754-7_2
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DOI: https://doi.org/10.1007/978-3-319-41754-7_2
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