PageRank in undirected random graphs
Résumé
PageRank has numerous applications in information retrieval, reputation systems, machine learning, and graph partitioning.
In this paper, we study PageRank in undirected random graphs with expansion property. The Chung-Lu random graph represents
an example of such graphs. We show that in the limit, as the size of the graph goes to infinity, PageRank can be represented by a mixture of the restart distribution and the vertex degree distribution.
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