Enhanced semantic refinement gate for RNN-based neural language generator

Tran, Van Khanh, Nguyen, Van-Tao and Nguyen, Le-Minh 2017, Enhanced semantic refinement gate for RNN-based neural language generator, in KSE 2017 : Proceedings of the 9th International Conference on Knowledge and Systems Engineering 2017, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 172-178, doi: 10.1109/kse.2017.8119454.

Attached Files
Name Description MIMEType Size Downloads

Title Enhanced semantic refinement gate for RNN-based neural language generator
Author(s) Tran, Van KhanhORCID iD for Tran, Van Khanh orcid.org/0000-0002-3445-2596
Nguyen, Van-Tao
Nguyen, Le-Minh
Conference name Knowledge and Systems Engineering. Conference (9th : 2017 : Hue, Vietnam)
Conference location Hue, Vietnam
Conference dates 2017/10/19 - 2017/10/21
Title of proceedings KSE 2017 : Proceedings of the 9th International Conference on Knowledge and Systems Engineering 2017
Editor(s) Nguyen, Thanh-Thuy
Le, Anh-Phuong
Tojo, Satoshi
Nguyen, Le-Minh
Phan, Xuan-Hieu
Publication date 2017
Series Knowledge and Systems Engineering Conference
Start page 172
End page 178
Total pages 7
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Keyword(s) Logic gates
Generators
Computational modeling
Training
Semantics
Mathematical model
ISBN 978-1-5386-3576-6
Language eng
DOI 10.1109/kse.2017.8119454
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2017, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30122165

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 22 Abstract Views, 6 File Downloads  -  Detailed Statistics
Created: Thu, 30 May 2019, 12:05:23 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.