Rui Zhang

Orcid: 0000-0002-2264-8735

Affiliations:
  • South China University of Technology, Department of Software Engineering, Guangzhou, China


According to our database1, Rui Zhang authored at least 12 papers between 2017 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2022
Automatic Arabic Grammatical Error Correction based on Expectation-Maximization routing and target-bidirectional agreement.
Knowl. Based Syst., 2022

2021
Predicting Emotion Reactions for Human-Computer Conversation: A Variational Approach.
IEEE Trans. Hum. Mach. Syst., 2021

Emotion-sensitive deep dyna-Q learning for task-completion dialogue policy learning.
Neurocomputing, 2021

Melodic Phrase Attention Network for Symbolic Data-based Music Genre Classification (Student Abstract).
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Learning Bi-directional Social Influence in Information Cascades using Graph Sequence Attention Networks.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Dynamic Reward-Based Dueling Deep Dyna-Q: Robust Policy Learning in Noisy Environments.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Emotional Text Generation Based on Cross-Domain Sentiment Transfer.
IEEE Access, 2019

Cascade2vec: Learning Dynamic Cascade Representation by Recurrent Graph Neural Networks.
IEEE Access, 2019

Network2Vec: Learning Node Representation Based on Space Mapping in Networks.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

2018
Learning to Converse Emotionally Like Humans: A Conditional Variational Approach.
Proceedings of the Natural Language Processing and Chinese Computing, 2018

MMCRD: An Effective Algorithm for Deploying Monitoring Point on Social Network.
Proceedings of the Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding, 2018

2017
Building Emotional Conversation Systems Using Multi-task Seq2Seq Learning.
Proceedings of the Natural Language Processing and Chinese Computing, 2017


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