Hybrid approach for Khmer unknown word POS guessing

New words are being created everyday and the lexicon is not large enough to cover all the words, unknown words become a serious problem in part-of-speech tagging. This paper presents a hybrid approach to handle the unknown word problem in Khmer part-of-speech tagging. The hybrid approach combined of rule-based model and trigram model makes use of both internal structure of the word and surrounding contextual information to predict the part-of-speech of unknown words. The proposed approach achieves 88.9% and 78.2% of accuracy on training and test data respectively.