面向中文文本分类的积极情感词自动提取

Zhen'gang Yu, N. Zhen, Ming Xu
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引用次数: 3

摘要

情绪分析的目的是自动预测情绪倾向。解决这一问题的传统方法大多基于监督学习,但费时且难以扩展。本文提出了一种基于非监督学习和语言规则的情感分析方法。没有必要事先有一个积极情绪字典,因为我们可以在处理评论时自动构建它。通过该积极情绪词典,为产品评论分类提供了一种有效的方法。由于该方法不依赖于领域,因此易于扩展。实验结果表明,该方法具有良好的应用前景。
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Automatic positive sentiment word extraction for Chinese text classification
Sentiment analysis aims to predict sentiment tendency automatically. Traditional methods tackling this problem are mostly based on supervised learning,but it is time-consuming and uneasy to extendable. In this paper,we provide a novel method of sentiment analysis based on un-supervised learning together with some language rules. It is no necessary to have a positive sentiment dictionary beforehand as we can build it automatically during processing the comments. By this positive sentiment dictionary,it provides an efficient way to classify the product reviews. The methodology presented is easy to extend due to its un-domain-dependency. As we can see,the experiment result obtained shows its promising application.
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