Title
Cross-lingual implicit discourse relation recognition with co-training.
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.
Year
DOI
Venue
2018
10.1631/FITEE.1601865
Frontiers of IT & EE
Keywords
Field
DocType
Cross-lingual, Implicit discourse relation recognition, Co-training, TP391.1
Discourse relation,Mathematical optimization,Cross lingual,Computer science,Machine translation,Co-training,Exploit,Natural language processing,Artificial intelligence
Journal
Volume
Issue
ISSN
19
5
2095-9184
Citations 
PageRank 
References 
1
0.35
0
Authors
6
Name
Order
Citations
PageRank
Yaojie Lu133.42
mu xu2510.29
ChangXing Wu372.11
Deyi Xiong484567.74
Hongji Wang591.12
Jinsong Su626041.51