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Multimedia Technology and Enhanced Learning. 4th EAI International Conference, ICMTEL 2022, Virtual Event, April 15-16, 2022, Proceedings

Research Article

Personalized Dialogue Generation Method of Chat Robot Based on Topic Perception

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-18123-8_43,
        author={Junmei Li},
        title={Personalized Dialogue Generation Method of Chat Robot Based on Topic Perception},
        proceedings={Multimedia Technology and Enhanced Learning. 4th EAI International Conference, ICMTEL 2022, Virtual Event, April 15-16, 2022, Proceedings},
        proceedings_a={ICMTEL},
        year={2022},
        month={10},
        keywords={Chatbot Personalization Dialogue generation},
        doi={10.1007/978-3-031-18123-8_43}
    }
    
  • Junmei Li
    Year: 2022
    Personalized Dialogue Generation Method of Chat Robot Based on Topic Perception
    ICMTEL
    Springer
    DOI: 10.1007/978-3-031-18123-8_43
Junmei Li1,*
  • 1: School of Computer Engineering, Jingchu University of Technology
*Contact email: chenweiliang7895@163.com

Abstract

Human-Computer interaction system is a significant research direction in the field of human-computer interaction, and the research of open domain chat robot has received extensive attention. There are many problems in the existing chat robot: lack of personalized features, resulting in the process of the same chat, and the conversation has nothing to do with the topic. Therefore, a method of creating personalized conversation based on topic perception is proposed, and a personalized conversation model based on topic perception is designed. Semantic analysis and text similarity calculation are needed to build a conversation model. Based on the dialogue model, the training robot collects the corpus data related to the subject, convolves the corpus data related to the subject, and carries out the topic perception training. Finally, a personalized dialogue mechanism is established to generate personalized dialogue. Through experimental comparison, it is proved that the dialogue generated by this method is more suitable for the chat topic.

Keywords
Chatbot Personalization Dialogue generation
Published
2022-10-19
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-18123-8_43
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