Reducing Parsing Complexity by Intra-Sentence Segmentation based on Maximum Entropy Model

Sung Dong Kim, Byoung-Tak Zhang, Yung Taek Kim


Anthology ID:
W00-1321
Volume:
2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora
Month:
October
Year:
2000
Address:
Hong Kong, China
Venues:
VLC | EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
164–171
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/W00-1321/
DOI:
10.3115/1117794.1117815
Bibkey:
Cite (ACL):
Sung Dong Kim, Byoung-Tak Zhang, and Yung Taek Kim. 2000. Reducing Parsing Complexity by Intra-Sentence Segmentation based on Maximum Entropy Model. In 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, pages 164–171, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Reducing Parsing Complexity by Intra-Sentence Segmentation based on Maximum Entropy Model (Kim et al., VLC-EMNLP 2000)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/W00-1321.pdf