A Gradual Refinement Model for A Robust Thai Morphological Analyzer

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 which 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. Frdm 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.

• Type: Conference
• Year: 1996
• Where: COLING
• Authors: Asanee Kawtrakul, Chalatip Thumkanon, Thitima Jamjanya, Parinee Muangyunnan, Kritsada Poolwan
• Keywords: COLING 1996, COLING 2008, Correct Part-of-speech Tag, Implicit Spelling Error, Syntactic Based Pruning