基于链接相似度和作弊系数的Spam网页识别算法

Spam网页主要通过链接作弊手段达到提高搜索排名而获利的目的,根据链接作弊的特征,引入链接相似度和作弊系数两个指标来判定网页作弊的可能性。借鉴BadRank算法思想,从Spam网页种子集合通过迭代计算链接相似度和作弊系数,并根据与种子集合的链接指向关系设置权重,将待判定的网页进行度量。最后选取Anti-Trust Rank等算法作对比实验,结果验证了本文算法在准确率和适应性方面优于对比算法。

An algorithm of identify spam pages based on link similarity and spam rates

Spam pages seek to boost their ranking positions and thus earn profit mainly through spam links. Based on the analytical features of spam links, we introduce link similarity and spam rate as two indexes for spam page judgment. Inspired by the Bad Rank algorithm, we calculate link similarity and Spam rate by iteration from the seed set of spam pages, set the weights in accordance with the relationship of link pointing from the seed set of spam pages, and measure the pages to be judged. Anti Trust Rank and other relevant approaches are adopted to make comparison with the traditional comparative methods. Experimental results prove the advantage of our approach over the traditional methods.