PageRank has become a key element in the success of search engines, allowing
to rank the most important hits in the top screen of results. One key aspect
that distinguishes PageRank from other prestige measures such as in-degree is
its global nature. From the information provider perspective, this makes it
difficult or impossible to predict how their pages will be ranked. Consequently
a market has emerged for the optimization of search engine results. Here we
study the accuracy with which PageRank can be approximated by in-degree, a
local measure made freely available by search engines. Theoretical and
empirical analyses lead to conclude that given the weak degree correlations in
the Web link graph, the approximation can be relatively accurate, giving
service and information providers an effective new marketing tool.
%0 Generic
%1 citeulike:383901
%A Fortunato, Santo
%A Boguna, Marian
%A Flammini, Alessandro
%A Menczer, Filippo
%D 2005
%K pagerank ten top
%T How to make the top ten: Approximating PageRank from in-degree
%U http://arxiv.org/abs/cs.IR/0511016
%X PageRank has become a key element in the success of search engines, allowing
to rank the most important hits in the top screen of results. One key aspect
that distinguishes PageRank from other prestige measures such as in-degree is
its global nature. From the information provider perspective, this makes it
difficult or impossible to predict how their pages will be ranked. Consequently
a market has emerged for the optimization of search engine results. Here we
study the accuracy with which PageRank can be approximated by in-degree, a
local measure made freely available by search engines. Theoretical and
empirical analyses lead to conclude that given the weak degree correlations in
the Web link graph, the approximation can be relatively accurate, giving
service and information providers an effective new marketing tool.
@misc{citeulike:383901,
abstract = {PageRank has become a key element in the success of search engines, allowing
to rank the most important hits in the top screen of results. One key aspect
that distinguishes PageRank from other prestige measures such as in-degree is
its global nature. From the information provider perspective, this makes it
difficult or impossible to predict how their pages will be ranked. Consequently
a market has emerged for the optimization of search engine results. Here we
study the accuracy with which PageRank can be approximated by in-degree, a
local measure made freely available by search engines. Theoretical and
empirical analyses lead to conclude that given the weak degree correlations in
the Web link graph, the approximation can be relatively accurate, giving
service and information providers an effective new marketing tool.},
added-at = {2007-08-18T13:22:24.000+0200},
author = {Fortunato, Santo and Boguna, Marian and Flammini, Alessandro and Menczer, Filippo},
biburl = {https://www.bibsonomy.org/bibtex/2ed89b5d64f186881a276eea7cfa66e46/a_olympia},
citeulike-article-id = {383901},
description = {citeulike},
eprint = {cs.IR/0511016},
interhash = {59a2c99dd2616c732eba8e5b4ae744b8},
intrahash = {ed89b5d64f186881a276eea7cfa66e46},
keywords = {pagerank ten top},
month = Nov,
priority = {2},
timestamp = {2007-08-18T13:22:41.000+0200},
title = {How to make the top ten: Approximating PageRank from in-degree},
url = {http://arxiv.org/abs/cs.IR/0511016},
year = 2005
}