Transformation Rule Learning without Rule Templates: A Case Study in Part of Speech Tagging

@article{Bach2008TransformationRL,
  title={Transformation Rule Learning without Rule Templates: A Case Study in Part of Speech Tagging},
  author={Ngo Xuan Bach and Le Anh Cuong and Nguyen Viet Ha and Nguyen Ngoc Binh},
  journal={2008 International Conference on Advanced Language Processing and Web Information Technology},
  year={2008},
  pages={9-14}
}
Part of speech (POS) tagging is an important problem and is one of the first steps included in many tasks in natural language processing. It affects directly on the accuracy of many other problems such as Syntax Parsing, WordSense Disambiguation, and Machine Translation. Stochastic models solve this problem relatively well, but they still make mistakes. Transformation-based learning (TBL) is a solution which can be used to improve stochastic taggers by learning a set of transformation rules… CONTINUE READING