DC Field | Value | Language |
---|---|---|
dc.contributor.author | oh, Jong-hun | - |
dc.contributor.author | Choi, Key-Sun | - |
dc.date.accessioned | 2008-07-14T04:55:52Z | - |
dc.date.available | 2008-07-14T04:55:52Z | - |
dc.date.issued | 2003-03 | - |
dc.identifier.citation | A maximum entropy approach to natural language processing, Vol. 16, No. 1, pp. 41–62 | en |
dc.identifier.uri | http://hdl.handle.net/10203/5713 | - |
dc.description.abstract | In this paper, we will describe a Korean transliterated foreign word extraction algorithm. In the proposed method, we reformulate the foreign word extraction problem as a syllable-tagging problem such that each syllable is tagged with a foreign syllable tag or a pure Korean syllable tag. Syllable sequences of Korean strings are modelled by Hidden Markov Model whose state represents a character with binary marking to indicate whether the syllable is part of a transliterated foreign word or not. The proposed method extracts a transliterated foreign word with high recall rate and precision rate. Moreover, our method shows good performance even with small-sized training corpora. | en |
dc.language.iso | en_US | en |
dc.publisher | World Scientific Publishing | en |
dc.subject | Computer Science | en |
dc.title | A Statistical Model for Automatic Extraction of Korean Transliterated | en |
dc.type | Thesis | en |
dc.identifier.doi | 10.1142/S021942790300084X | - |
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