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Available viahttp://dbpubs.stanford.edu/pub/2003-20
Submitted on 11th of March 2003
Author Haveliwala, Taher; Kamvar, Sepandar
Title The Second Eigenvalue of the Google Matrix
Date of publication 2003
Published in Stanford University Technical Report
Citation Haveliwala, Taher; Kamvar, Sepandar. The Second Eigenvalue of the Google Matrix, Stanford University Technical Report
Number of pages 8
Language English
Project Stanford InfoLab; Database Group; Natural Language Processing Group
Type Technical Report
Subject group Computer Science; Data Mining; Databases and the Web; Miscellaneous
Abstract We determine analytically the modulus of the second eigenvalue for the web hyperlink matrix used by Google for computing PageRank. Specifically, we prove the following statement: ``For any matrix $A=[cP + (1-c)E]^T$, where $P$ is an $n \times n$ row-stochastic matrix, $E$ is a strictly positive $n \times n$ rank-one row-stochastic matrix, and $0 \leq c \leq 1$, the second eigenvalue of $A$ has modulus $|\lambda_2| \leq c$. Furthermore, if $P$ has at least two irreducible closed subsets, the second eigenvalue $\lambda_2 = c$.'' This statement has implications for the convergence rate of the standard PageRank algorithm as the web scales, for the stability of PageRank to perturbations to the link structure of the web, for the detection of Google spammers, and for the design of algorithms to speed up PageRank.
Keywords PageRank, eigenvalue, markov chain
Contact address taherh@cs.stanford.edu
sdkamvar@stanford.edu
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