Web spam classification
Miklós Erdélyi, András Garzó, András A. Benczúr · 2011
In this paper we investigate how much various classes of Web spam features, some requiring very high computational effort, add to the classification accuracy. We realize that advances in machine learning, an area that has received less attention in the adversarial IR community, yields more improvement than new features and result in low cost yet accurate spam filters. Our original contributions are as follows: