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Research on Medical Dialogue Generation of External Knowledge


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QIN Libo, LI Zhouyang, LOU Jieming, YU Qiying, CHI Wanxiang. Review of research progress on natural language generation in task-based dialogue systems [J]. Journal of Chinese Information Technology, 2022. Libo Qin Zhouyang Li Jieming Lou Qiying Yu Wanxiang Chi Review of research progress on natural language generation in task-based dialogue systems [J] . Journal of Chinese Information Technology , 2022 . Search in Google Scholar

ZHANG Xiaoyu, LI Dongdong, REN Pengjie, CHEN Zhumin, MA Jun, REN Zhaochun. Knowledge-aware medical dialogue generation based on memory network [J]. Computer Research and Development, 2022. Xiaoyu Zhang Dongdong Li Pengjie Ren Zhumin Chen Jun Ma Zhaochun Ren Knowledge-aware medical dialogue generation based on memory network [J] . Computer Research and Development , 2022 . Search in Google Scholar

Wen T H, Gasic M, Kim D, et al. Stochastic language generation in dialogue using recurrent neural networks with convolutional sentence reranking [J]. 2015. Wen T H Gasic M Kim D Stochastic language generation in dialogue using recurrent neural networks with convolutional sentence reranking [J] . 2015 . Search in Google Scholar

Wen T H, Gasic M, Mrksic N, et al. Semantically conditioned lstm-based natural language generation for spoken dialogue systems [J]. 1508.01745, 2015. Wen T H Gasic M Mrksic N Semantically conditioned lstm-based natural language generation for spoken dialogue systems [J] . 1508.01745, 2015 . Search in Google Scholar

Dušek O, Jurčíček F. Sequence-to-sequence generation for spoken dialogue via deep syntax trees and strings [J]. 2016. Dušek O Jurčíček F. Sequence-to-sequence generation for spoken dialogue via deep syntax trees and strings [J] . 2016 Search in Google Scholar

Dušek O, Jurčíček F. A context-aware natural language generator for dialogue systems [J]. 2016. Dušek O Jurčíček F. A context-aware natural language generator for dialogue systems [J] . 2016 . Search in Google Scholar

Tran V K, Nguyen L M. Neural-based natural language generation in dialogue using rnn encoder-decoder with semantic aggregation [J]. 2017. Tran V K Nguyen L M. Neural-based natural language generation in dialogue using rnn encoder-decoder with semantic aggregation [J] . 2017 . Search in Google Scholar

Wei Z, Liu Q, Peng B, et al. Task-oriented dialogue system for automatic diagnosis[C]//Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 2018: 201–207. Wei Z Liu Q Peng B Task-oriented dialogue system for automatic diagnosis[C] // Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) . 2018 : 201 207 . Search in Google Scholar

Su S Y, Huang C W, Chen Y N. Dual supervised learning for natural language understanding and generation [J]. 2019. Su S Y Huang C W Chen Y N. Dual supervised learning for natural language understanding and generation [J] . 2019 . Search in Google Scholar

Peng B, Zhu C, Li C, et al. Few-shot natural language generation for task-oriented dialog [J]. 2020. Peng B Zhu C Li C Few-shot natural language generation for task-oriented dialog [J] . 2020 . Search in Google Scholar

Li Y, Yao K. Interpretable nlg for task-oriented dialogue systems with heterogeneous rendering machines[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2021, 35(15): 13306–13314. Li Y Yao K. Interpretable nlg for task-oriented dialogue systems with heterogeneous rendering machines[C] // Proceedings of the AAAI Conference on Artificial Intelligence . 2021 , 35 ( 15 ): 13306 13314 . Search in Google Scholar

Sutskever I, Vinyals O, Le Q V. Sequence to sequence learning with neural networks [J]. Advances in neural information processing systems, 2014, 27. Sutskever I Vinyals O Le Q V. Sequence to sequence learning with neural networks [J] . Advances in neural information processing systems , 2014 , 27 . Search in Google Scholar

Radford A, Narasimhan K, Salimans T, et al. Improving language understanding by generative pre-training [J]. 2018. Radford A Narasimhan K Salimans T Improving language understanding by generative pre-training [J] . 2018 . Search in Google Scholar

Radford A, Wu J, Child R, et al. Language models are unsupervised multitask learners [J]. 2019, 1(8). Radford A Wu J Child R Language models are unsupervised multitask learners [J] . 2019 , 1 ( 8). Search in Google Scholar

eISSN:
2470-8038
Język:
Angielski
Częstotliwość wydawania:
4 razy w roku
Dziedziny czasopisma:
Computer Sciences, other