A Bayesian Model for Morpheme and Paradigm Identification

@inproceedings{Snover2001ABM,
  title={A Bayesian Model for Morpheme and Paradigm Identification},
  author={Matthew G. Snover and M. Brent},
  booktitle={ACL},
  year={2001}
}
This paper describes a system for unsupervised learning of morphological affixes from texts or word lists. The system is composed of a generative probability model and a search algorithm. Experiments on the Wall Street Journal and the Hansard Corpus (French and English) demonstrate the effectiveness of this approach. The results suggest that more integrated systems for learning both affixes and morphographemic adjustment rules may be feasible. In addition, several definitions and a theorem are… Expand
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