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Pagerank Revisited (2006) [10 citations — 1 self]

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@MISC{Brinkmeier06pagerankrevisited,
    author = {Michael Brinkmeier},
    title = {Pagerank Revisited},
    year = {2006}
}

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Abstract:

PageRank, one part of the search engine Google, is one of the most prominent link-based rankings of documents in the World Wide Web. Usually it is described as a Markov Chain modelling a specific random surfer. In this paper an alternative representation as a power series is given. Nonetheless it is possible to interpret the values as probabilities in a random surfer setting, di#ering from the usual one.

Citations

1839	The Anatomy of a Large-Scale Hypertextual Web Search Engine – Brin, Page - 1998
1064	The PageRank Citation Ranking: Bringing Order to the Web – Page, Brin, et al. - 1999
229	Topic-sensitive PageRank – Haveliwala - 2002
134	Scaling personalized web search – Jeh, Widom - 2003
98	Extrapolation methods for accelerating PageRank computations – Kamvar, Haveliwala, et al. - 2003
85	SimRank: A measure of structural-context similarity – Jeh, Widom - 2002
84	Exploiting the Block Structure of the Web for Computing PageRank – Kamvar, Haveliwala, et al. - 2003
44	Topic-sensitive pagerank: A contextsensitive ranking algorithm for web search – Haveliwala
42	PageRank computation and the structure of the Web: experiments and algorithms – Arasu, Novak, et al. - 2002
42	The Second Eigenvalue of the Google Matrix – Haveliwala, Kamvar - 2003
37	Adaptive methods for the computation of pagerank – Kamvar, Haveliawala, et al. - 2003
33	An Analytical Comparison of Approaches to Personalizing Pagerank – Haveliwala, Kamvar, et al. - 2003
2	E-mail address: mbrinkme@tu-ilmenau.de – Webgraph