Chinese Review Spam Classification Using Machine Learning Method

Yahui Xi
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引用次数: 7

Abstract

With great development of the e-commerce, the number of product reviews grows rapidly on the e-commerce website. Review mining has recently received a lot of attention, which aims to discover valuable information from the massive product reviews. An important subject of review mining is review spam classification, which classifies reviews into reviews or spam reviews, offering high-quality data to review mining. In this paper, we first present a categorization of Chinese review spam, and then classify the reviews by using machine learning method with different features, finally analyze the impact of different features on classification performance. The experiments show that Chinese review spam classification will obtain high accuracy by using machine learning method with appropriate features.
基于机器学习方法的中文评论垃圾分类
随着电子商务的迅猛发展,电子商务网站上的产品评论数量迅速增长。评论挖掘最近受到了广泛的关注,其目的是从海量的产品评论中发现有价值的信息。评论垃圾分类是评论挖掘的一个重要课题,它将评论分类为评论或垃圾评论,为评论挖掘提供高质量的数据。本文首先对中文评论垃圾进行分类,然后利用机器学习方法对不同特征的评论进行分类,最后分析不同特征对分类性能的影响。实验表明,采用适当特征的机器学习方法可以获得较高的中文评论垃圾邮件分类准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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