Improving Spam Link Detection based on Graph for Search Engine Result

Abstract

Web deals with huge, diverse, unstructured and dynamic data. The Search Engines are
thus an effective way to fetch users query result. Spam poses a significant role in misguiding the web
users utilizing spamming techniques on content and link. Thus we need a development of effective
and efficient tool that can serve this purpose and thereby minimizes the effect of spam. Link spam
can be filtered efficiently using graph based detection. In Graphs based classification nodes are web
pages and links are hyperlinks to redirect .It employs calculation of PageRank and Normalized
PageRank based on mean value of the traditional PageRank algorithm that filters the spam pages.
The resultant numeric value employed is used to obtain rank the page and generate the graph.