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A Variant of Updating Page Rank in Evolving Tree graphs
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Department of Mathematics, School of Physical Sciences, Makerere University, Kampala, Uganda. (MAM)
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Department of Mathematics, College of Natural and Applied Sciences, University of Dar es Salaam,Tanzania. (MAM)
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0002-1624-5147
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Department of Mathematics, Makerere University, Kampala, Uganda. (MAM)
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2019 (English)In: Proceedings of 18th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop, Florence, Italy: 11-14 June, 2019 / [ed] Christos H. Skiadas, ISAST: International Society for the Advancement of Science and Technology , 2019, p. 31-49Conference paper, Published paper (Refereed)
Abstract [en]

PageRank update refers to the process of computing new PageRank values after change(s) (addition or removal of links/vertices) has occurred in real life networks. The purpose of the updating is to avoid recalculating the values from scratch. To efficiently carry out the update, we consider PageRank as the expected number of visits to target vertex if multiple random walks are performed, starting at each vertex once and weighing each of these walks by a weight value. Hence, it might be looked at as updating non-normalised PageRank. In the proposed approach, a scaled adjacency matrix is sequentially updated after every change and the levels of the vertices being updated as well. This enables sets of internal and sink vertices dependent on their roots or parents, thus vector-vector product can be performed sequentially since there are no infinite steps from one vertex to the other.

Place, publisher, year, edition, pages
ISAST: International Society for the Advancement of Science and Technology , 2019. p. 31-49
Keywords [en]
PageRank, randomwalk, graph, networks.
National Category
Probability Theory and Statistics Computational Mathematics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-47083ISBN: 978-618-5180-33-1 (electronic)OAI: oai:DiVA.org:mdh-47083DiVA, id: diva2:1394753
Conference
ASMDA2019, 18th Applied Stochastic Models and Data Analysis International Conference
Funder
Sida - Swedish International Development Cooperation AgencyAvailable from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-02-24Bibliographically approved

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http://www.asmda.es/

Authority records BETA

Abola, BenardBiganda, PitosEngström, ChristopherAnguzu, CollinsSilvestrov, Sergei

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