An Efficient Algorithm for Unsupervised Word Segmentation with Branching Entropy and MDL-Reference-Cited by-同舟云学术

An Efficient Algorithm for Unsupervised Word Segmentation with Branching Entropy and MDL

Published:2013 Issue:3 Volume:28 Page:347-360
ISSN:1346-0714
Container-title:Transactions of the Japanese Society for Artificial Intelligence
language:en
Short-container-title:Transactions of the Japanese Society for Artificial Intelligence

Author:

Zhikov Valentin¹,Takamura Hiroya²,Okumura Manabu²

Affiliation:

1. Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology(Currently, Valentin Zhikov works for Ontotext AD in Bulgaria.)

2. Precision and Intelligence Laboratory, Tokyo Institute of Technology

Publisher

Japanese Society for Artificial Intelligence

Subject

Artificial Intelligence,Software

Link

https://www.jstage.jst.go.jp/article/tjsai/28/3/28_347/_pdf

Reference31 articles.

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2. [Brent 96] Brent, M. R. and Cartwright, T. A.: Distributional Regularity and Phonotactic Constraints are Useful for Segmentation, Cognition, Vol. 61, No. 1--2, pp. 93--125 (1996)

3. [Cao 08] Cao, Y., Duan, H., Lin, C.-Y., Yu, Y., and Hon, H.-W.: Recommending questions using the mdl-based tree cut model, in Proceedings of the 17th international conference on World Wide Web, pp. 81--90 (2008)

4. [Creutz 02] Creutz, M. and Lagus, K.: Unsupervised discovery of morphemes, in Proceedings of the ACL-02 workshop on Morphological and phonological learning, pp. 21--30 (2002)

5. [Emerson 05] Emerson, T.: The second international Chinese word segmentation bakeoff, in Proceedings of the Fourth SIGHAN Workshop on Chinese Language Processing, pp. 123--133 (2005)

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