CLC number: TP391.1
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2018-05-08
Cited: 0
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Yao-jie Lu, Mu Xu, Chang-xing Wu, De-yi Xiong, Hong-ji Wang, Jin-song Su. Cross-lingual implicit discourse relation recognition with co-training[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(5): 651-661.
@article{title="Cross-lingual implicit discourse relation recognition with co-training",
author="Yao-jie Lu, Mu Xu, Chang-xing Wu, De-yi Xiong, Hong-ji Wang, Jin-song Su",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="19",
number="5",
pages="651-661",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601865"
}
%0 Journal Article
%T Cross-lingual implicit discourse relation recognition with co-training
%A Yao-jie Lu
%A Mu Xu
%A Chang-xing Wu
%A De-yi Xiong
%A Hong-ji Wang
%A Jin-song Su
%J Frontiers of Information Technology & Electronic Engineering
%V 19
%N 5
%P 651-661
%@ 2095-9184
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601865
TY - JOUR
T1 - Cross-lingual implicit discourse relation recognition with co-training
A1 - Yao-jie Lu
A1 - Mu Xu
A1 - Chang-xing Wu
A1 - De-yi Xiong
A1 - Hong-ji Wang
A1 - Jin-song Su
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 19
IS - 5
SP - 651
EP - 661
%@ 2095-9184
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1601865
Abstract: A lack of labeled corpora obstructs the research progress on implicit discourse relation recognition (DRR) for Chinese, while there are some available discourse corpora in other languages, such as English. In this paper, we propose a cross-lingual implicit DRR framework that exploits an available English corpus for the Chinese DRR task. We use machine translation to generate Chinese instances from a labeled English discourse corpus. In this way, each instance has two independent views: Chinese and English views. Then we train two classifiers in Chinese and English in a co-training way, which exploits unlabeled Chinese data to implement better implicit DRR for Chinese. Experimental results demonstrate the effectiveness of our method.
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