What should I Ask: A Knowledge-driven Approach for Follow-up Questions Generation in Conversational Surveys

Yubin Ge, Ziang Xiao, Jana Diesner, Heng Ji, Karrie Karahalios, Hari Sundaram


Anthology ID:
2023.paclic-1.12
Volume:
Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation
Month:
December
Year:
2023
Address:
Hong Kong, China
Editors:
Chu-Ren Huang, Yasunari Harada, Jong-Bok Kim, Si Chen, Yu-Yin Hsu, Emmanuele Chersoni, Pranav A, Winnie Huiheng Zeng, Bo Peng, Yuxi Li, Junlin Li
Venue:
PACLIC
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
113–124
Language:
URL:
https://aclanthology.org/2023.paclic-1.12
DOI:
Bibkey:
Cite (ACL):
Yubin Ge, Ziang Xiao, Jana Diesner, Heng Ji, Karrie Karahalios, and Hari Sundaram. 2023. What should I Ask: A Knowledge-driven Approach for Follow-up Questions Generation in Conversational Surveys. In Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation, pages 113–124, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
What should I Ask: A Knowledge-driven Approach for Follow-up Questions Generation in Conversational Surveys (Ge et al., PACLIC 2023)
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PDF:
https://preview.aclanthology.org/ingest-2024-clasp/2023.paclic-1.12.pdf