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LREC
2010

AutoTagTCG : A Framework for Automatic Thai CG Tagging

13 years 5 months ago
AutoTagTCG : A Framework for Automatic Thai CG Tagging
Recently, categorical grammar has been focused as a powerful grammar. This paper aims to develop a framework for automatic CG tagging for Thai. We investigated two main algorithms, CRF and Statistical alignment model based on information theory (SAM). We found that SAM gives the best results both in word level and sentence level. We got the accuracy 89.25% in word level and 82.49% in sentence level. SAM is better than CRF in known word. On the other hand, CRF is better than SAM when we applied for unknown word. Combining both methods can be suited for both known and unknown word.
Thepchai Supnithi, Taneth Ruangrajitpakorn, Kanoko
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where LREC
Authors Thepchai Supnithi, Taneth Ruangrajitpakorn, Kanokorn Trakultaweekool, Peerachet Porkaew
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