@inproceedings{e9cbdf6f8b8a46748546e84b583a7ec3,
title = "On using ensemble methods for Chinese named entity recognition",
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.",
author = "Wu, {Chia Wei} and Jan, {Shyh Yi} and Tsai, {Richard Tzong Han} and Hsu, {Wen Lian}",
note = "Publisher Copyright: {\textcopyright} 2006 Association for Computational Linguistics.; null ; Conference date: 22-07-2006 Through 23-07-2006",
year = "2006",
language = "???core.languages.en_GB???",
series = "COLING/ACL 2006 - 5th SIGHAN Workshop on Chinese Language Processing, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "142--145",
booktitle = "COLING/ACL 2006 - 5th SIGHAN Workshop on Chinese Language Processing, Proceedings of the Workshop",
}