You know about PageRank and about two weeks ago I mentioned a new paper from Stanford’s Database Group discussing PeopleRank. Today, another paper posted on the Stanford server. This one introduces TrustRank that has been developed to help fight web spam. Here’s the abstract:
Web spam pages use various techniques to achieve higher-than-deserved rankings in a search engine’s results. While human experts can identify spam, it is too expensive to manually evaluate a large number of pages. Instead, we propose techniques to semi-automatically separate reputable, good pages from spam. We first select a small set of seed pages to be evaluated by an expert. Once we manually identify the reputable seed pages, we use the link structure of the web to discover other pages that are likely to be good. In this paper we discuss possible ways to implement the seed selection and the discovery of good pages. We present results of experiments run on the World Wide Web indexed by AltaVista and evaluate the performance of our techniques. Our results show that we can effectively filter out spam from a significant fraction of the web, based on a good seed set of less than 200 sites.
Another version of the paper was published in March 2004.
The full text of the paper: Combating Web Spam with TrustRank is available as a 12 page PDF. It was co-authored by Zoltan Gyongyi (Stanford), Hector Garcia-Molina (Stanford) and Jan Pedersen (Yahoo!).