Movie Review Classification Based on a Multiple Classifier
Movie Review Classification Based on a Multiple Classifier
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发表时间：
2007-11
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通讯作者：
Kimitaka Tsutsumi;Kazutaka Shimada;Tsutomu Endo
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作者：
Kimitaka Tsutsumi;Kazutaka Shimada;Tsutomu Endo
在本文中，我们提出了一种方法来分类电影评论文件到积极或消极的意见。有几种方法可以对文档进行分类。然而，以前的研究，只使用一个分类器的分类任务。我们描述了一个多分类器的审查文件分类任务。该方法由三个分类器基于支持向量机，ME和得分计算。我们将两种投票方法和支持向量机应用到单分类器的集成过程中。与三个单一分类器相比，集成方法提高了准确率。实验结果表明了该方法的有效性。
In this paper, we propose a method to classify movie review documents into positive or negative opinions. There are several approaches to classify documents. The previous studies, however, used only a single classifier for the classification task. We describe a multiple classifier for the review document classification task. The method consists of three classifiers based on SVMs, ME and score calculation. We apply two voting methods and SVMs to the integration process of single classifiers. The integrated methods improved the accuracy as compared with the three single classifiers. The experimental results show the effectiveness of our method.