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Machine Translation : 13th China Workshop, CWMT 2017, Dalian, China, September 27-29, 2017, Revised Selected Papers / edited by Derek F. Wong, Deyi Xiong.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Wong, Derek F., editor.
Xiong, Deyi, editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Communications in computer and information science 1865-0929 ; 787.
Communications in Computer and Information Science, 1865-0929 ; 787
Language:
English
Subjects (All):
Natural language processing (Computer science).
Artificial intelligence.
Natural Language Processing (NLP).
Artificial Intelligence.
Local Subjects:
Natural Language Processing (NLP).
Artificial Intelligence.
Physical Description:
1 online resource (XI, 125 pages) : 25 illustrations.
Edition:
First edition 2017.
Contained In:
Springer eBooks
Place of Publication:
Singapore : Springer Singapore : Imprint: Springer, 2017.
System Details:
text file PDF
Summary:
This book constitutes the refereed proceedings of the 13th China Workshop on Machine Translation, CWMT 2017, held in Dalian, China, in September 2017. The 10 papers presented in this volume were carefully reviewed and selected from 26 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Contents:
Neural Machine Translation with Phrasal Attention
Singleton Detection for Coreference Resolution via Multi-window and Multi-Filter CNN
A Method of Unknown Words Processing for Neural Machine Translation Using HowNet
Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMT
An Unknown Word Processing Method in NMT by Integrating Syntactic Structure and Semantic Concept
RGraph: Generating Reference Graphs for Better Machine Translation Evaluation
ENTF: An Entropy-based MT Evaluation Metric
Translation Oriented Sentence Level Collocation Identification and Extraction
Combining Domain Knowledge and Deep Learning Makes NMT More Adaptive
Handling Many-To-One UNK Translation for Neural Machine Translation
A Content-based Neural Reordering Model for Statistical Machine Translation. .
Other Format:
Printed edition:
ISBN:
978-981-10-7134-8
9789811071348
Access Restriction:
Restricted for use by site license.

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