Knowledge graph assisted end-to-end medical dialog generation

Author:

Varshney DeekshaORCID,Zafar Aizan,Behera Niranshu Kumar,Ekbal Asif

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference70 articles.

1. Hua K, Feng Z, Tao C, Yan R, Zhang L. Learning to detect relevant contexts and knowledge for response selection in retrieval-based dialogue systems. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management. 2020, p. 525–34.

2. Vakulenko S, Kanoulas E, de Rijke M. An analysis of mixed initiative and collaboration in information-seeking dialogues. In: Proceedings of the 43rd International ACM SIGIR Conference on research and development in information retrieval. 2020, p. 2085–8.

3. Topical-chat: Towards knowledge-grounded open-domain conversations;Gopalakrishnan,2019

4. Zhao Y, Wu W, Xu C. Are pre-trained language models knowledgeable to ground open domain dialogues?, arXiv preprint arXiv:2011.09708.

5. Wu C-S, Socher R, Xiong C. Global-to-local memory pointer networks for task-oriented dialogue. In: International Conference on learning representations. 2018.

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