Augmenting Dialogue Response Generation With Unstructured Textual Knowledge

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...

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Bibliographic Details
Main Authors: Yanmeng Wang, Wenge Rong, Yuanxin Ouyang, Zhang Xiong
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Dialogue response generation
unstructured knowledge
knowledge embedding
attentive reader
Online Access:https://ieeexplore.ieee.org/document/8665913/

Internet

https://ieeexplore.ieee.org/document/8665913/

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