PageRank: A modified random surfer model

PageRank is an approach to evaluate the importance of a web page implemented by Google. It is one of the important system features that Google used in order to improve the quality of search result in the original version of Google apart from utilizing link (anchor) in web pages. The success of Google has led to various researches on the theory behind Google search. PageRank is one of the theories that are studied over the years by researchers. Various theories are proposed to enhance PageRank in terms of its quality and computation time. This paper explains the behavior of Markov chain involved in a random surfer model from the original PageRank. A modified random surfer model is proposed, which could lead to a more predictable time for computing PageRank.