Augmenting Dialogue Response Generation With Unstructured Textual Knowledge
The dialogue response generation is a challenging task in chatbot applications. Recently neural-network-based dialogue models, including the sequence-to-sequence model and the RNN language models, are able to generate fluent and grammatically compliant responses, while there is a major limitation th...
Main Authors: | Yanmeng Wang, Wenge Rong, Yuanxin Ouyang, Zhang Xiong |
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Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8665913/ |
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