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Using Graph Partitioning to Calculate PageRank in a Changing Network
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0003-4554-6528
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0002-1624-5147
2019 (English)In: Data Analysis and Applications 2: Utilization of Results in Europe and Other Topics / [ed] Christos H. Skiadas, James R. Bozeman, London, UK: John Wiley & Sons, 2019, p. 179-191Chapter in book (Refereed)
Abstract [en]

PageRank was first defined by S. Brin and L. Page in 1998 in order to rank home pages on the Internet by ranking pages according to the stationary distribution of a random walk on the web graph. While the original way to calculate PageRank is fast, due to the huge size and growth of the web there have been many attempts at improving upon the calculation speed of PageRank through various means. In this article we will look at a slightly different but equally important problem, namely how to improve the calculation of PageRank in a changing network where PageRank of an earlier stage of the network is available. In particular, we consider two types of changes in the graph, the change in rank after changing the personalization vector used in calculating PageRank as well as added or removed edges between different strongly connected components in the network.

Place, publisher, year, edition, pages
London, UK: John Wiley & Sons, 2019. p. 179-191
Keywords [en]
PageRank, networks, graphs
National Category
Computational Mathematics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-42715ISBN: 9781786304476 (print)OAI: oai:DiVA.org:mdh-42715DiVA, id: diva2:1289335
Available from: 2019-02-17 Created: 2019-02-17 Last updated: 2019-02-26Bibliographically approved

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