Automatic Opinion Question Generation

Yllias Chali, Tina Baghaee


Abstract
We study the problem of opinion question generation from sentences with the help of community-based question answering systems. For this purpose, we use a sequence to sequence attentional model, and we adopt coverage mechanism to prevent sentences from repeating themselves. Experimental results on the Amazon question/answer dataset show an improvement in automatic evaluation metrics as well as human evaluations from the state-of-the-art question generation systems.
Anthology ID:
W18-6518
Volume:
Proceedings of the 11th International Conference on Natural Language Generation
Month:
November
Year:
2018
Address:
Tilburg University, The Netherlands
Editors:
Emiel Krahmer, Albert Gatt, Martijn Goudbeek
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
152–158
Language:
URL:
https://aclanthology.org/W18-6518
DOI:
10.18653/v1/W18-6518
Bibkey:
Cite (ACL):
Yllias Chali and Tina Baghaee. 2018. Automatic Opinion Question Generation. In Proceedings of the 11th International Conference on Natural Language Generation, pages 152–158, Tilburg University, The Netherlands. Association for Computational Linguistics.
Cite (Informal):
Automatic Opinion Question Generation (Chali & Baghaee, INLG 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/ml4al-ingestion/W18-6518.pdf
Code
 Tina-19/Question-Generation