Topic-level knowledge sub-graphs for multi-turn dialogue generation

Author:

Li Jing,Huang QingbaoORCID,Cai Yi,Liu Yongkang,Fu Mingyi,Li Qing

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference48 articles.

1. A memory network based end-to-end personalized task-oriented dialogue generation;Zhang;Knowl. Based Syst.,2020

2. ReCoSa: Detecting the relevant contexts with self-attention for multi-turn dialogue generation;Zhang,2019

3. A hierarchical recurrent encoder-decoder for generative context-aware query suggestion;Sordoni,2015

4. Dual dynamic memory network for end-to-end multi-turn task-oriented dialog systems;Wang,2020

5. Modeling topical relevance for multi-turn dialogue generation;Zhang,2020

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1. Building knowledge-grounded dialogue systems with graph-based semantic modelling;Knowledge-Based Systems;2024-08

2. Empathetic Dialogue Generation with Contrastive Learning and Multi-Source Information Fusion;2023 IEEE 14th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP);2023-11-24

3. SPK-CG: Siamese Network based Posterior Knowledge Selection Model for Knowledge Driven Conversation Generation;ACM Transactions on Asian and Low-Resource Language Information Processing;2023-03-10

4. EAGS: An extracting auxiliary knowledge graph model in multi-turn dialogue generation;World Wide Web;2022-09-30

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