Novel Features for Web Spam Detection
Santosh Kumar, Xiaoying Gao, Ian S. Welch · 2016
Recent research on web spam detection has shown promising results, and many new and efficient detection algorithms have been developed. While most research focuses on developing algorithms, our investigation shows that the features used in the algorithms are in fact very important, and different features can lead to very different results. This paper investigates three types of web spam, content-based, link-based and cloaking, and introduces new features for identifying the three types of spam. Our experimental results show that the introduction of new features significantly improves the detection performance.