A Spamicity Approach to Web Spam Detection

Web spam which refers to any deliberate actions bringing to selected web pages an unjustifiable favorable relevance or importance is one of the major obstacles for high quality information retrieval on the web. Most of the existing web spam detection methods are supervised that require a large and representative training set of web pages. Moreover, they often assume some global information such as a large web graph and snapshots of a large collection of web pages. However, in many situations such assumptions may not hold. This paper studies the problem of unsupervised web spam detection. They introduce the notion of spamicity to measure how likely a page is spam.