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Nonparametric Analysis of Extremes on Web Graphs : PageRank Versus Max-Linear Model
Markovich, Natalia M.; Ryzhov, Maxim; Krieger, Udo R. (2017): Nonparametric Analysis of Extremes on Web Graphs : PageRank Versus Max-Linear Model, in: Vladimir M. Vishnevskiy, Konstantin E. Samouylov, und Dmitry V. Kozyrev (Hrsg.), Distributed Computer and Communication Networks : 20th International Conference, DCCN 2017, Moscow, Russia, September 25–29, 2017, Proceedings, Cham: Springer International Publishing, S. 13–26, doi: 10.1007/978-3-319-66836-9_2.
Faculty/Chair:
Author:
Title of the compilation:
Distributed Computer and Communication Networks : 20th International Conference, DCCN 2017, Moscow, Russia, September 25–29, 2017, Proceedings
Conference:
20th International Conference, DCCN 2017, September 25–29, 2017 ; Moscow, Russia
Publisher Information:
Year of publication:
2017
Pages:
ISBN:
978-3-319-66836-9
978-3-319-66835-2
Language:
English
Abstract:
We analyze the cluster structure in large networks by means of clusters of exceedances regarding the influence characteristics of nodes. As the latter characteristics we use PageRank and the Max-Linear model and compare their distributions and dependence structure. Due to the heaviness of tail and dependence of PageRank and Max-Linear model observations, the influence indices appear by clusters or conglomerates of nodes grouped around influential nodes. The mean size of such clusters is determined by a so called extremal index. It is related to the tail index that indicates the heaviness of the distribution tail. We consider graphs of Web pages and partition them into clusters of nodes by their influence.
Keywords: ; ; ; ;
Web graph
PageRank
Max-Linear model
Extremal index
Tail index
International Distribution:
Yes:
Type:
Conferenceobject
Activation date:
November 27, 2017
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https://fis.uni-bamberg.de/handle/uniba/42842