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Automatic Positive Sentiment Word Extraction for Chinese Text Classification

机译:中国文本分类的自动积极情感词提取

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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 unsupervised 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.
机译:情绪分析旨在自动预测情绪趋势。解决这个问题的传统方法主要是基于监督学习,但它对可延伸是耗时和不安的。在本文中,我们提供了一种基于无监督学习的语言规则的情绪分析方法。事先没有必要在处理评论期间自动构建积极的情感字典。通过这种积极的情感词典,它提供了对产品评论进行分类的有效方法。由于其未域依赖性而呈现的方法易于扩展。正如我们所看到的,所获得的实验结果显示了其有前途的应用。

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