Updating pagerank with iterative aggregation No sign up no membership no email sex chat

Posted by / 24-Dec-2017 03:07

Updating pagerank with iterative aggregation

The purpose of the paper is to present some convergence properties of the iterative aggregation–disaggregation method for computing a stationary probability distribution vector of a column stochastic matrix.

A sufficient condition for the local convergence property and the corresponding rate of convergence are established.

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Computing Google’s Page Rank via lumping the Google matrix was recently analyzed in [I.

In this note, we show that the reduced matrix obtained by lumping the dangling nodes can be further reduced by lumping a class of nondangling nodes, called weakly nondangling nodes, to another single node, and the further reduced matrix is also stochastic with the same nonzero eigenvalues as the Google matrix.

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It was shown that all of the dangling nodes can be lumped into a single node and the Page Rank could be obtained by applying the power method to the reduced matrix.