UM  > 科技學院  > 電腦及資訊科學系
Graph-based semi-supervised model for joint Chinese word segmentation and part-of-speech tagging
Zeng X.2; Wong D.F.2; Chao L.S.2; Trancoso I.1
2013
Conference Namethe 51st Annual Meeting of the Association for Computational Linguistics
Source PublicationProceedings of the 51st Annual Meeting of the Association for Computational Linguistics
Volume1
Pages770-779
Conference DateAugust 4-9 2013
Conference PlaceSofia, Bulgaria
Abstract

This paper introduces a graph-based semisupervised joint model of Chinese word segmentation and part-of-speech tagging. The proposed approach is based on a graph-based label propagation technique. One constructs a nearest-neighbor similarity graph over all trigrams of labeled and unlabeled data for propagating syntactic information, i.e., label distributions. The derived label distributions are regarded as virtual evidences to regularize the learning of linear conditional random fields (CRFs) on unlabeled data. An inductive character-based joint model is obtained eventually. Empirical results on Chinese tree bank (CTB-7) and Microsoft Research corpora (MSR) reveal that the proposed model can yield better results than the supervised baselines and other competitive semi-supervised CRFs in this task. © 2013 Association for Computational Linguistics.

URLView the original
Language英语
Fulltext Access
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Instituto Superior Técnico
2.Universidade de Macau
Recommended Citation
GB/T 7714
Zeng X.,Wong D.F.,Chao L.S.,et al. Graph-based semi-supervised model for joint Chinese word segmentation and part-of-speech tagging[C],2013:770-779.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zeng X.]'s Articles
[Wong D.F.]'s Articles
[Chao L.S.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zeng X.]'s Articles
[Wong D.F.]'s Articles
[Chao L.S.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zeng X.]'s Articles
[Wong D.F.]'s Articles
[Chao L.S.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.