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ORCIDNEWS@ACL 2015: Beijing, China
- Xiangyu Duan, Rafael E. Banchs, Min Zhang, Haizhou Li, A. Kumaran:
Proceedings of the Fifth Named Entity Workshop, NEWS@ACL 2015, Beijing, China, July 31, 2015. Association for Computational Linguistics 2015, ISBN 978-1-941643-65-5 - Min Zhang, Haizhou Li, Rafael E. Banchs, A. Kumaran:
Whitepaper of NEWS 2015 Shared Task on Machine Transliteration. 1-9 - Rafael E. Banchs, Min Zhang, Xiangyu Duan, Haizhou Li, A. Kumaran:
Report of NEWS 2015 Machine Transliteration Shared Task. 10-23 - Greg Kondrak:
How do you spell that? A journey through word representations. 24 - Cícero Nogueira dos Santos, Victor Guimarães:
Boosting Named Entity Recognition with Neural Character Embeddings. 25-33 - Oi Yee Kwong:
Regularity and Flexibility in English-Chinese Name Transliteration. 34-42 - Livy Real, Alexandre Rademaker:
HAREM and Klue: how to put two tagsets for named entities annotation together. 43-49 - Quang Hong Pham, Minh Le Nguyen, Binh T. Nguyen, Nguyen Viet Cuong:
Semi-supervised Learning for Vietnamese Named Entity Recognition using Online Conditional Random Fields. 50-55 - Yan Shao, Jörg Tiedemann, Joakim Nivre:
Boosting English-Chinese Machine Transliteration via High Quality Alignment and Multilingual Resources. 56-60 - Andrew M. Finch, Lemao Liu, Xiaolin Wang, Eiichiro Sumita:
Neural Network Transduction Models in Transliteration Generation. 61-66 - Dandan Wang, Xiaohui Yang, Jinan Xu, Yufeng Chen, Nan Wang, Bojia Liu, Jian Yang, Yujie Zhang:
A Hybrid Transliteration Model for Chinese/English Named Entities - BJTU-NLP Report for the 5th Named Entities Workshop. 67-71 - Garrett Nicolai, Bradley Hauer, Mohammad Salameh, Adam St. Arnaud, Ying Xu, Lei Yao, Grzegorz Kondrak:
Multiple System Combination for Transliteration. 72-77 - Anoop Kunchukuttan, Pushpak Bhattacharyya:
Data representation methods and use of mined corpora for Indian language transliteration. 78-82 - Yu-Chun Wang, Chun-Kai Wu, Richard Tzong-Han Tsai:
NCU IISR English-Korean and English-Chinese Named Entity Transliteration Using Different Grapheme Segmentation Approaches. 83-87
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