Human–Machine Multi-Turn Language Dialogue Interaction Based on Deep Learning

During multi-turn dialogue, with the increase in dialogue turns, the difficulty of intention recognition and the generation of the following sentence reply become more and more difficult. This paper mainly optimizes the context information extraction ability of the Seq2Seq Encoder in multi-turn dial...

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Detalles Bibliográficos
Autores principales: Ke, Xianxin, Hu, Ping, Yang, Chenghao, Zhang, Renbao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955483/
https://www.ncbi.nlm.nih.gov/pubmed/35334647
http://dx.doi.org/10.3390/mi13030355

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955483/
https://www.ncbi.nlm.nih.gov/pubmed/35334647
http://dx.doi.org/10.3390/mi13030355

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