Redundancy reduction as a strategy for unsupervised learning
Neural Computation
Inference of variable-length linguistic and acoustic units by multigrams
Speech Communication
An Efficient, Probabilistically Sound Algorithm for Segmentation andWord Discovery
Machine Learning - Special issue on natural language learning
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
Unsupervised learning of the morphology of a natural language
Computational Linguistics
Knowledge-free induction of morphology using latent semantic analysis
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Unsupervised discovery of morphemes
MPL '02 Proceedings of the ACL-02 workshop on Morphological and phonological learning - Volume 6
MPL '02 Proceedings of the ACL-02 workshop on Morphological and phonological learning - Volume 6
A framework for unsupervised natural language morphology induction
ACLstudent '04 Proceedings of the ACL 2004 workshop on Student research
Induction of a simple morphology for highly-inflecting languages
SIGMorPhon '04 Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology
| Hi-index | 0.00 |
This paper reports the present results of a research on unsupervised Persian morpheme discovery. In this paper we present a method for discovering the morphemes of Persian language through automatic analysis of corpora. We utilized a Minimum Description Length (MDL) based algorithm with some improvements and applied it to Persian corpus. Our improvements include enhancing the cost function using some heuristics, preventing the split of high frequency chunks, exploiting penalty for first and last letters and distinguishing pre-parts and post-parts. Our improved approach has raised the precision, recall and f-measure of discovery by respectively %32, %17 and %23.