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A Novel Chinese Text Mining Method for E-Commerce Review Spam Detection

机译:电子商务评论垃圾邮件检测的中文文本挖掘新方法

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Review spam is increasingly rampant in China, which seriously hampers the development of the vigorous e-commerce market. In this paper, we propose a novel Chinese text mining method to detect review spam automatically and efficiently. We correctly extract keywords in complicated review text and conduct fine-grained analysis to recognize the semantic orientation. We study the spammers' behavior patterns and come up with four effective features to describe untruthful comments. We train classifier to classify reviews into spam or non-spam. Experiments are conducted to demonstrate the excellent performance of our algorithm.
机译:评论垃圾邮件在中国日益猖,,严重阻碍了蓬勃发展的电子商务市场的发展。在本文中,我们提出了一种新颖的中文文本挖掘方法,可以自动,高效地检测评论垃圾邮件。我们会正确提取复杂评论文本中的关键字,并进行细粒度分析以识别语义方向。我们研究了垃圾邮件发送者的行为模式,并提出了四个有效的功能来描述不真实的评论。我们训练分类器将评论分类为垃圾邮件或非垃圾邮件。进行实验以证明我们算法的出色性能。

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