Title
Using PageRank to Characterize Web Structure
Abstract
Recent work on modeling the Web graph has dwelt on capturing the degree distributions observed on the Web. Pointing out that this represents a heavy reliance on "local" properties of the Web graph, we study the distribution of PageRank values (used in the Google search engine) on the Web. This distribution is of independent interest in optimizing search indices and storage. We show that PageRank values on the Web follow a power law. We then develop detailed models for the Web graph that explain this observation, and moreover remain faithful to previously studied degree distributions. We analyze these models, and compare the analyses to both snapshots from the Web and to graphs generated by simulations on the new models. To our knowledge this represents the first modeling of the Web that goes beyond fitting degree distributions on the Web.
Year
DOI
Venue
2002
10.1007/3-540-45655-4_36
Internet Mathematics
Keywords
Field
DocType
characterize web structure,web graph,google search engine,fitting degree distribution,degree distribution,independent interest,detailed model,new model,heavy reliance,optimizing search index,pagerank value,power law
Graph,PageRank,Search engine,Computer science,Directed graph,Theoretical computer science,Web structure,Snapshot (computer storage),Power law,Distributed computing,The Internet
Conference
Volume
Issue
ISSN
3
1
1542-7951
ISBN
Citations 
PageRank 
3-540-43996-X
73
6.37
References 
Authors
10
4
Name
Order
Citations
PageRank
Gopal Pandurangan192178.62
Prabhakar Raghavan2133512776.61
Eli Upfal34310743.13
p gopal4736.37