Statistical Language Learning
Probabilistic tagging with feature structures
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
A stochastic Japanese morphological analyzer using a forward-DP backward-A* N-best search algorithm
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Syllable-based model for the Korean morphology
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Segmenting a sentence into morphemes using statistic information between words
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
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This work attempts to provide a robust Thai morphological analyzer which can automatically assign the correct part-of-speech tag to the correct word with time and space efficiency. Instead of using a corpus based approach with requires a large amount of training data and validation data, a new simple hybrid technique which incorporates heuristic, syntactic and semantic knowledge is proposed. To implement this technique, a three-stage approach is adopted to the gradual refinement module. It consists of preference based pruning, syntactic based pruning and semantic based pruning, Each stage will gradually weeds out word boundary ambiguities, tag ambiguities and implicit spelling errors. From the result of the experiment, the proposed model can work with time-efficiency and increase the accuracy of word boundary segmentations, POS tagging as well as implicit spelling error correction.