Empirical Study of Unsupervised Chinese Word Segmentation Methods for SMT on Large-scale Corpora

Xiaolin Wang, Masao Utiyama, Andrew Finch, Eiichiro Sumita


Anthology ID:
P14-2122
Volume:
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
June
Year:
2014
Address:
Baltimore, Maryland
Editors:
Kristina Toutanova, Hua Wu
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
752–758
Language:
URL:
https://aclanthology.org/P14-2122
DOI:
10.3115/v1/P14-2122
Bibkey:
Cite (ACL):
Xiaolin Wang, Masao Utiyama, Andrew Finch, and Eiichiro Sumita. 2014. Empirical Study of Unsupervised Chinese Word Segmentation Methods for SMT on Large-scale Corpora. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 752–758, Baltimore, Maryland. Association for Computational Linguistics.
Cite (Informal):
Empirical Study of Unsupervised Chinese Word Segmentation Methods for SMT on Large-scale Corpora (Wang et al., ACL 2014)
Copy Citation:
PDF:
https://aclanthology.org/P14-2122.pdf
Video:
 https://aclanthology.org/P14-2122.mp4