UM  > Faculty of Science and Technology
Ensemble Learning on Portuguese POS Tagging
Xiao-Dong ZENG; Sam CHAO; Fai WONG
2011
Conference NameIII SIMELP Simpósio Mundial de Estudos de Língua Portguguesa, SIMPÓSIO 46 - Propostas Integração de Metodologias para o Estudo do Processo Tradutório
Source PublicationIn III SIMELP Simpósio Mundial de Estudos de Língua Portguguesa, SIMPÓSIO 46 - Propostas Integração de Metodologias para o Estudo do Processo Tradutório.
Conference Date2011
Conference PlaceMacau, China
Abstract

Ensemble learning, also known as multiple classifier system, can combine the predictions from multiple base classifiers/learners altogether to conclude a final decision. It has been proven that ensemble learning is a simple, useful and effective meta-classification methodology. SBCB (Selecting Base Classifiers on Bagging) is a selective based ensemble learning algorithm which is able to select an optimal set of classifiers amongst all base classifiers in determining the final result. SBCB equips with an optimization process that is capable of selecting a suitable number of optimal classifiers among all base classifiers automatically, in which, diversity and accuracy are considered as two major selection criteria. In this paper, we built a part-of-speech (POS) tagger for Portuguese based on SBCB learning algorithm as a case study to further investigate the effectiveness and performance of SBCB algorithm. The problem of POS tagging is a practical issue in natural language processing (NLP), especially in the development of a machine translation system. The performance of the POS tagging may interference the subsequent analytical tasks in the translation process, and thereafter affects the translation quality. The POS tagging task can be regarded as a classification problem. Features such as the surrounding context of ambiguous candidates, n-gram information, lexical items and linguistic clues are used and automatically extracted from the Portuguese annotated corpus. The empirical results reveal the effectiveness of SBCB 1 Faculty of Science and Technology, University of Macau Av. Padre Tomás Pereira, Taipa, Macau nlp2ct.samuel@gmail.com, {lidiasc, derekfw }@umac.mo algorithm on POS tagging.

KeywordEnsemble Learning Classifier Selection Pos Tagging Sbcb
Language英语
Fulltext Access
Document TypeConference paper
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationFaculty of Science and Technology, University of Macau
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Xiao-Dong ZENG,Sam CHAO,Fai WONG. Ensemble Learning on Portuguese POS Tagging[C],2011.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xiao-Dong ZENG]'s Articles
[Sam CHAO]'s Articles
[Fai WONG]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xiao-Dong ZENG]'s Articles
[Sam CHAO]'s Articles
[Fai WONG]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xiao-Dong ZENG]'s Articles
[Sam CHAO]'s Articles
[Fai WONG]'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.