@inproceedings{dai-etal-2021-ji,
title = "基于信息交互增强的时序关系联合识别(Joint Recognition of Temporal Relation Based on Information Interaction Enhancement)",
author = "Dai, Qianying and
Kong, Fang",
editor = "Li, Sheng and
Sun, Maosong and
Liu, Yang and
Wu, Hua and
Liu, Kang and
Che, Wanxiang and
He, Shizhu and
Rao, Gaoqi",
booktitle = "Proceedings of the 20th Chinese National Conference on Computational Linguistics",
month = aug,
year = "2021",
address = "Huhhot, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2021.ccl-1.72",
pages = "803--812",
abstract = "时序关系识别是信息抽取领域的一个重要分支,对文本理解发挥着关键作用。按照关联对象的不同,时序关系分为三大类:事件对(E-E)间的时序关系,事件与时间表达式间(E-T)的时序关系,事件与文档建立时间(E-D)间的时序关系。不同关系类型孤立识别的方法忽视了其间隐含的关联信息,针对这一问题构建了基于信息交互增强的时序关系联合识别模型。通过在不同神经网络层之间共享参数实现E-E与E-T时序关系的语义交流,利用两者的潜在联系提高识别精度。在Time-Bank Dense语料上的一系列实验表明,该方法优于现有的大多数神经网络方法。",
language = "Chinese",
}
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<abstract>时序关系识别是信息抽取领域的一个重要分支,对文本理解发挥着关键作用。按照关联对象的不同,时序关系分为三大类:事件对(E-E)间的时序关系,事件与时间表达式间(E-T)的时序关系,事件与文档建立时间(E-D)间的时序关系。不同关系类型孤立识别的方法忽视了其间隐含的关联信息,针对这一问题构建了基于信息交互增强的时序关系联合识别模型。通过在不同神经网络层之间共享参数实现E-E与E-T时序关系的语义交流,利用两者的潜在联系提高识别精度。在Time-Bank Dense语料上的一系列实验表明,该方法优于现有的大多数神经网络方法。</abstract>
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%0 Conference Proceedings
%T 基于信息交互增强的时序关系联合识别(Joint Recognition of Temporal Relation Based on Information Interaction Enhancement)
%A Dai, Qianying
%A Kong, Fang
%Y Li, Sheng
%Y Sun, Maosong
%Y Liu, Yang
%Y Wu, Hua
%Y Liu, Kang
%Y Che, Wanxiang
%Y He, Shizhu
%Y Rao, Gaoqi
%S Proceedings of the 20th Chinese National Conference on Computational Linguistics
%D 2021
%8 August
%I Chinese Information Processing Society of China
%C Huhhot, China
%G Chinese
%F dai-etal-2021-ji
%X 时序关系识别是信息抽取领域的一个重要分支,对文本理解发挥着关键作用。按照关联对象的不同,时序关系分为三大类:事件对(E-E)间的时序关系,事件与时间表达式间(E-T)的时序关系,事件与文档建立时间(E-D)间的时序关系。不同关系类型孤立识别的方法忽视了其间隐含的关联信息,针对这一问题构建了基于信息交互增强的时序关系联合识别模型。通过在不同神经网络层之间共享参数实现E-E与E-T时序关系的语义交流,利用两者的潜在联系提高识别精度。在Time-Bank Dense语料上的一系列实验表明,该方法优于现有的大多数神经网络方法。
%U https://aclanthology.org/2021.ccl-1.72
%P 803-812
Markdown (Informal)
[基于信息交互增强的时序关系联合识别(Joint Recognition of Temporal Relation Based on Information Interaction Enhancement)](https://aclanthology.org/2021.ccl-1.72) (Dai & Kong, CCL 2021)
ACL