On using ensemble methods for Chinese named entity recognition

Chia Wei Wu, Shyh Yi Jan, Richard Tzong Han Tsai, Wen Lian Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

In sequence labeling tasks, applying different machine learning models and feature sets usually leads to different results. In this paper, we exploit two ensemble methods in order to integrate multiple results generated under different conditions. One method is based on majority vote, while the other is a memory-based approach that integrates maximum entropy and conditional random field classifiers. Our results indicate that the memory-based method can outperform the individual classifiers, but the majority vote method cannot.

Original languageEnglish
Title of host publicationCOLING/ACL 2006 - 5th SIGHAN Workshop on Chinese Language Processing, Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages142-145
Number of pages4
ISBN (Electronic)1932432701, 9781932432701
StatePublished - 2006
Event5th SIGHAN Workshop on Chinese Language Processing, co-located with COLING/ACL 2006 - Sydney, Australia
Duration: 22 Jul 200623 Jul 2006

Publication series

NameCOLING/ACL 2006 - 5th SIGHAN Workshop on Chinese Language Processing, Proceedings of the Workshop

Conference

Conference5th SIGHAN Workshop on Chinese Language Processing, co-located with COLING/ACL 2006
Country/TerritoryAustralia
CitySydney
Period22/07/0623/07/06

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