@inproceedings{jiayi-etal-2024-triple,
title = "Triple-view Event Hierarchy Model for Biomedical Event Representation",
author = "Jiayi, Huang and
Lishuang, Li and
Xueyang, Qin and
Yi, Xiang and
Jiaqi, Li and
Yubo, Feng",
editor = "Sun, Maosong and
Liang, Jiye and
Han, Xianpei and
Liu, Zhiyuan and
He, Yulan",
booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)",
month = jul,
year = "2024",
address = "Taiyuan, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2024.ccl-1.88/",
pages = "1136--1147",
language = "eng",
abstract = "{\textquotedblleft}Biomedical event representation can be applied to various language tasks. A biomedical eventoften involves multiple biomedical entities and trigger words, and the event structure is complex.However, existing research on event representation mainly focuses on the general domain. Ifmodels from the general domain are directly transferred to biomedical event representation, theresults may not be satisfactory. We argue that biomedical events can be divided into three hierar-chies, each containing unique feature information. Therefore, we propose the Triple-views EventHierarchy Model (TEHM) to enhance the quality of biomedical event representation. TEHM ex-tracts feature information from three different views and integrates them. Specifically, due to thecomplexity of biomedical events, We propose the Trigger-aware Aggregator module to handlecomplex units within biomedical events. Additionally, we annotate two similarity task datasetsin the biomedical domain using annotation standards from the general domain. Extensive exper-iments demonstrate that TEHM achieves state-of-the-art performance on biomedical similaritytasks and biomedical event casual relation extraction.Introduction{\textquotedblright}"
}
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<abstract>“Biomedical event representation can be applied to various language tasks. A biomedical eventoften involves multiple biomedical entities and trigger words, and the event structure is complex.However, existing research on event representation mainly focuses on the general domain. Ifmodels from the general domain are directly transferred to biomedical event representation, theresults may not be satisfactory. We argue that biomedical events can be divided into three hierar-chies, each containing unique feature information. Therefore, we propose the Triple-views EventHierarchy Model (TEHM) to enhance the quality of biomedical event representation. TEHM ex-tracts feature information from three different views and integrates them. Specifically, due to thecomplexity of biomedical events, We propose the Trigger-aware Aggregator module to handlecomplex units within biomedical events. Additionally, we annotate two similarity task datasetsin the biomedical domain using annotation standards from the general domain. Extensive exper-iments demonstrate that TEHM achieves state-of-the-art performance on biomedical similaritytasks and biomedical event casual relation extraction.Introduction”</abstract>
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%0 Conference Proceedings
%T Triple-view Event Hierarchy Model for Biomedical Event Representation
%A Jiayi, Huang
%A Lishuang, Li
%A Xueyang, Qin
%A Yi, Xiang
%A Jiaqi, Li
%A Yubo, Feng
%Y Sun, Maosong
%Y Liang, Jiye
%Y Han, Xianpei
%Y Liu, Zhiyuan
%Y He, Yulan
%S Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)
%D 2024
%8 July
%I Chinese Information Processing Society of China
%C Taiyuan, China
%G eng
%F jiayi-etal-2024-triple
%X “Biomedical event representation can be applied to various language tasks. A biomedical eventoften involves multiple biomedical entities and trigger words, and the event structure is complex.However, existing research on event representation mainly focuses on the general domain. Ifmodels from the general domain are directly transferred to biomedical event representation, theresults may not be satisfactory. We argue that biomedical events can be divided into three hierar-chies, each containing unique feature information. Therefore, we propose the Triple-views EventHierarchy Model (TEHM) to enhance the quality of biomedical event representation. TEHM ex-tracts feature information from three different views and integrates them. Specifically, due to thecomplexity of biomedical events, We propose the Trigger-aware Aggregator module to handlecomplex units within biomedical events. Additionally, we annotate two similarity task datasetsin the biomedical domain using annotation standards from the general domain. Extensive exper-iments demonstrate that TEHM achieves state-of-the-art performance on biomedical similaritytasks and biomedical event casual relation extraction.Introduction”
%U https://aclanthology.org/2024.ccl-1.88/
%P 1136-1147
Markdown (Informal)
[Triple-view Event Hierarchy Model for Biomedical Event Representation](https://aclanthology.org/2024.ccl-1.88/) (Jiayi et al., CCL 2024)
ACL
- Huang Jiayi, Li Lishuang, Qin Xueyang, Xiang Yi, Li Jiaqi, and Feng Yubo. 2024. Triple-view Event Hierarchy Model for Biomedical Event Representation. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference), pages 1136–1147, Taiyuan, China. Chinese Information Processing Society of China.