UETrice at MEDIQA 2021: A Prosper-thy-neighbour Extractive Multi-document Summarization Model

Duy-Cat Can, Quoc-An Nguyen, Quoc-Hung Duong, Minh-Quang Nguyen, Huy-Son Nguyen, Linh Nguyen Tran Ngoc, Quang-Thuy Ha, Mai-Vu Tran


Abstract
This paper describes a system developed to summarize multiple answers challenge in the MEDIQA 2021 shared task collocated with the BioNLP 2021 Workshop. We propose an extractive summarization architecture based on several scores and state-of-the-art techniques. We also present our novel prosper-thy-neighbour strategies to improve performance. Our model has been proven to be effective with the best ROUGE-1/ROUGE-L scores, being the shared task runner up by ROUGE-2 F1 score (over 13 participated teams).
Anthology ID:
2021.bionlp-1.36
Volume:
Proceedings of the 20th Workshop on Biomedical Language Processing
Month:
June
Year:
2021
Address:
Online
Venues:
BioNLP | NAACL
SIG:
SIGBIOMED
Publisher:
Association for Computational Linguistics
Note:
Pages:
311–319
Language:
URL:
https://aclanthology.org/2021.bionlp-1.36
DOI:
10.18653/v1/2021.bionlp-1.36
Bibkey:
Cite (ACL):
Duy-Cat Can, Quoc-An Nguyen, Quoc-Hung Duong, Minh-Quang Nguyen, Huy-Son Nguyen, Linh Nguyen Tran Ngoc, Quang-Thuy Ha, and Mai-Vu Tran. 2021. UETrice at MEDIQA 2021: A Prosper-thy-neighbour Extractive Multi-document Summarization Model. In Proceedings of the 20th Workshop on Biomedical Language Processing, pages 311–319, Online. Association for Computational Linguistics.
Cite (Informal):
UETrice at MEDIQA 2021: A Prosper-thy-neighbour Extractive Multi-document Summarization Model (Can et al., BioNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.bionlp-1.36.pdf