Identifying Web Spam with the Wisdom of the Crowds
Identifying Web Spam with the Wisdom of the Crowds
复制标题
利用群众的智慧识别网络垃圾邮件
DOI：
10.1145/2109205.2109207
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发表时间：
2012-03-01
影响因子：
3.5
通讯作者：
Ru, Liyun
中科院分区：
文献类型：
--
作者：
Liu, Yiqun;Chen, Fei;Ru, Liyun
打击网络垃圾邮件已经成为网络搜索引擎面临的最大挑战之一。最先进的垃圾邮件检测技术通常是针对特定的已知类型的Web垃圾邮件而设计的，无法有效地处理新出现的垃圾邮件类型。通过对Web访问日志中用户行为的分析，提出了一种基于学习机制的垃圾页面检测算法。主要贡献如下。(1)研究了垃圾网页的用户访问模式，提出了一系列区分垃圾网页和普通网页的用户行为特征。(2)提出了一种新的垃圾邮件检测框架，通过对用户行为的分析，可以检测出各种类型的垃圾邮件，包括新出现的垃圾邮件。在大规模实际Web访问日志数据上的实验表明，所提出的特征和检测框架是有效的。
Combating Web spam has become one of the top challenges for Web search engines. State-of-the-art spam-detection techniques are usually designed for specific, known types of Web spam and are incapable of dealing with newly appearing spam types efficiently. With user-behavior analyses from Web access logs, a spam page-detection algorithm is proposed based on a learning scheme. The main contributions are the following. (1) User-visiting patterns of spam pages are studied, and a number of user-behavior features are proposed for separating Web spam pages from ordinary pages. (2) A novel spam-detection framework is proposed that can detect various kinds of Web spam, including newly appearing ones, with the help of the user-behavior analysis. Experiments on large-scale practical Web access log data show the effectiveness of the proposed features and the detection framework.