Low cost page quality factors to detect web spam
Information Retrieval
2014-10-09 v1
Abstract
Web spam is a big challenge for quality of search engine results. It is very important for search engines to detect web spam accurately. In this paper we present 32 low cost quality factors to classify spam and ham pages on real time basis. These features can be divided in to three categories: (i) URL features, (ii) Content features, and (iii) Link features. We developed a classifier using Resilient Back-propagation learning algorithm of neural network and obtained good accuracy. This classifier can be applied to search engine results on real time because calculation of these features require very little CPU resources.
Keywords
Cite
@article{arxiv.1410.2085,
title = {Low cost page quality factors to detect web spam},
author = {Ashish Chandra and Mohammad Suaib and Dr. Rizwan Beg},
journal= {arXiv preprint arXiv:1410.2085},
year = {2014}
}