Automatic Term Name Generation for Gene Ontology: Task and Dataset

Yanjian Zhang, Qin Chen, Yiteng Zhang, Zhongyu Wei, Yixu Gao, Jiajie Peng, Zengfeng Huang, Weijian Sun, Xuanjing Huang


Abstract
Terms contained in Gene Ontology (GO) have been widely used in biology and bio-medicine. Most previous research focuses on inferring new GO terms, while the term names that reflect the gene function are still named by the experts. To fill this gap, we propose a novel task, namely term name generation for GO, and build a large-scale benchmark dataset. Furthermore, we present a graph-based generative model that incorporates the relations between genes, words and terms for term name generation, which exhibits great advantages over the strong baselines.
Anthology ID:
2020.findings-emnlp.422
Original:
2020.findings-emnlp.422v1
Version 2:
2020.findings-emnlp.422v2
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4705–4710
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.422
DOI:
10.18653/v1/2020.findings-emnlp.422
Bibkey:
Cite (ACL):
Yanjian Zhang, Qin Chen, Yiteng Zhang, Zhongyu Wei, Yixu Gao, Jiajie Peng, Zengfeng Huang, Weijian Sun, and Xuanjing Huang. 2020. Automatic Term Name Generation for Gene Ontology: Task and Dataset. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4705–4710, Online. Association for Computational Linguistics.
Cite (Informal):
Automatic Term Name Generation for Gene Ontology: Task and Dataset (Zhang et al., Findings 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.findings-emnlp.422.pdf