A probabilistic algorithm for segmenting non-Kanji Japanese strings
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Word association norms, mutual information, and lexicography
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
A statistical approach to language translation
COLING '88 Proceedings of the 12th 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
Automatic semantic sequence extraction from unrestricted non-tagged texts
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Entropy as an indicator of context boundaries: an experiment using a web search engine
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
The pwc connection machine: an adaptive expertise provider
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
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It is obvious that segmentation takes an important role in natural language processing(NLP), especially for the languages whose sentences are not easily separated into morphemes. In this study we propose a method of segmenting a sentence. The system described in this paper does not use any grammatical information or knowledge in processing. Instead, it uses statistical information drawn from non-tagged corpus of the target language. Most of the segmenting systems are to pick out conventional morphemes which is defined for human use. However, we still do not know whether those conventional morphemes are good units for computational processing.In this paper we explain our system's algorithm and its experimental results on Japanese, though this system is not designed for a particular language.