Google's success in the past years is strongly connected with its web search delivering precise results to queries. Over 200 factors are taken into account before the resulting pages are listed according to an overall relevancy score. One of the factors is the PageRank, which is a numerical value used to establish an importance ranking between all the web pages.
This paper tries to give a brief overview of the PageRank algorithm and its related topics. In section 2 the basic concepts and a first definition of PageRank are introduced. Due to problems arising with the simple model, the random surfer model leading to the Google matrix is depicted in section 3. Section 4 deals with convergence and sensitivity issues of the PageRank vector. The computation of the PageRank vector using different methods is shown in section 5.
-
Upload your own papers! Earn money and win an iPhone X. -
Upload your own papers! Earn money and win an iPhone X. -
Upload your own papers! Earn money and win an iPhone X. -
Upload your own papers! Earn money and win an iPhone X. -
Upload your own papers! Earn money and win an iPhone X.