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Issue No. 01 - January/February (2007 vol. 22)
ISSN: 1541-1672
pp: 28-35
Do-Gil Lee , Korea University
Hae-Chang Rim , Korea University
Dongsuk Yook , Korea University
Automatic word spacing decides the correct boundaries between words in a sentence. Word spacing is important in Korean, and word spacing errors are frequent. Several proposed probabilistic word-spacing models resolve problems with previous statistical approaches. These models regard automatic word spacing as a classification problem similar to part-of-speech tagging. By generalizing hidden Markov models, the models can consider a broader context and estimate more accurate probabilities. The authors tested these models under a wide range of conditions to compare them with the state of the art and performed detailed error analysis of them.
word spacing, probabilistic models, hidden Markov models, n-gram, machine learning

D. Yook, D. Lee and H. Rim, "Automatic Word Spacing Using Probabilistic Models Based on Character n-grams," in IEEE Intelligent Systems, vol. 22, no. , pp. 28-35, 2007.
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