On the mathematical background of Google PageRank algorithm

Alberto Peretti and Alberto Roveda ()

No 25/2014, Working Papers from University of Verona, Department of Economics

Abstract: The PageRank algorithm, the kernel of the method used by Google Search to give us the answer of a search we are asking in the web, contains a lot of mathematics. Maybe one could say that graphs and Markov chains theories are in the background, while the crucial steps are in a linear algebra context, as the eigenvalues of a matrix are involved. In this working paper we deal with all the mathematics we need to explain how the PageRank method works.

Keywords: Graph theory; Linear mappings; Eigenvalues; Markov chains. (search for similar items in EconPapers)
JEL-codes: C65 (search for similar items in EconPapers)
Pages: 19
Date: 2014-12
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Citations: View citations in EconPapers (3)

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