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NTIS 바로가기정보과학회논문지 = Journal of KIISE, v.41 no.9, 2014년, pp.642 - 651
This paper proposes three probabilistic models for syllable-based Korean morphological analysis, and presents the performance of proposed probabilistic models. Probabilities for the models are acquired from POS-tagged corpus. The result of 10-fold cross-validation experiments shows that 98.3% answer...
Jae Sung Lee, "Three-Step Probabilistic Model for Korean Morphological Analysis," Journal of KIISE : Software and Applications, Vol. 38, No. 5, pp. 257-268, 2011. (in Korean)
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Kwangseob Shim and Jaehyung Yang, "MACH : A Supersonic Korean Morphological Analyzer," Proceedings of the 19th International Conference on Computational Linguistics, pp. 939-945, 2002.
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Chung-Hye Han and Martha Palmer, "A Morphological Tagger for Korean: Statistical Tagging Combined with Corpus-Based Morphological Rule Application," Machine Translation, Vol. 18, pp. 275-297, 2005.
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Kwangseob Shim, "Morpheme Restoration for Syllable-based Korean POS Tagging," Journal of KIISE : Software and Applications, Vol. 40, No. 3, pp. 182-189, 2013. (in Korean)
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The National Institute of the Korean Language, 21st Century Sejong Project Final Result, 2011.12 Revised Edition, 2011. (in Korean)
D. Lee, B. Kim and J.S. Lee, "Language Model Smoothing for Korean Morpheme Recovery," Proceedings of KIISE, Vol. 39, No. 1B, pp. 309-311, 2012. (in Korean)
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