Biomedical Concept Normalization by Leveraging Hypernyms

Cheng Yan, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yafei Shi, Shengping Liu


Abstract
Biomedical Concept Normalization (BCN) is widely used in biomedical text processing as a fundamental module. Owing to numerous surface variants of biomedical concepts, BCN still remains challenging and unsolved. In this paper, we exploit biomedical concept hypernyms to facilitate BCN. We propose Biomedical Concept Normalizer with Hypernyms (BCNH), a novel framework that adopts list-wise training to make use of both hypernyms and synonyms, and also employs norm constraint on the representation of hypernym-hyponym entity pairs. The experimental results show that BCNH outperforms the previous state-of-the-art model on the NCBI dataset.
Anthology ID:
2021.emnlp-main.284
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3512–3517
Language:
URL:
https://aclanthology.org/2021.emnlp-main.284
DOI:
10.18653/v1/2021.emnlp-main.284
Bibkey:
Cite (ACL):
Cheng Yan, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yafei Shi, and Shengping Liu. 2021. Biomedical Concept Normalization by Leveraging Hypernyms. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 3512–3517, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Biomedical Concept Normalization by Leveraging Hypernyms (Yan et al., EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.284.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.284.mp4
Code
 yan-cheng/bcnh