Incorporating weight properties in detection of web spam

A. G. K. Leng, K. P. Ravi, Ashutosh Kumar Singh
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引用次数: 2

Abstract

This paper focus on incorporating weight properties to enhance Web spam detection algorithms. Our proposed methodology adds this feature into Anti-TrustRank algorithm and call it weighted Anti-TrustRank algorithm to show the effectiveness of the weight properties using a new metric. Experiments are conducted on WEBSPAM-UK2006, a public Web spam dataset and have shown that weighted Anti-TrustRank significantly outperforms Anti-TrustRank algorithm up to 37.85%.
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结合权重属性在检测网络垃圾邮件
本文的重点是结合权重属性来增强Web垃圾邮件检测算法。我们提出的方法将这一特征添加到Anti-TrustRank算法中,并将其称为加权Anti-TrustRank算法,以使用新的度量来显示权重属性的有效性。在WEBSPAM-UK2006(一个公开的Web垃圾邮件数据集)上进行的实验表明,加权Anti-TrustRank算法的性能显著优于Anti-TrustRank算法,达到37.85%。
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