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A Comparison of Graph Centrality Measures Based on Lazy Random Walks
Department of Mathematics, Makerere University, Kampala, Uganda.
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. (MAM)ORCID iD: 0000-0003-4554-6528
2021 (English)In: Applied Modeling Techniquesand Data Analysis 1: Computational Data AnalysisMethods and Tools / [ed] Yannis Dimotikalis, Alex Karagrigoriou, Christina Parpoula, Christos H Skiadas, John Wiley & Sons, Inc. Hoboken, NJ, USA , 2021, Vol. 7, p. 91-111Chapter in book (Refereed)
Abstract [en]

When working with a network, it is often of interest to locate the “most important”nodes in the network. A common way to do this is by using some graph centralitymeasures. Since what constitutes as an important node varies from one network toanother, or even in applications on the same network, there is a large number ofdifferent centrality measures proposed in the literature. Due to the large amount ofdifferent centrality measures proposed in different fields, there is also a large amountof very similar or equivalent centrality measures (in the sense that they give the sameranks). In this chapter, we focus on the centrality measures based on powers of theadjacency matrix and those based on random walk. In this case, we show how someof these centrality measures are related, as well as their lazy variants.We will performsome experiments to demonstrate the similarities between the centrality measures.

Place, publisher, year, edition, pages
John Wiley & Sons, Inc. Hoboken, NJ, USA , 2021. Vol. 7, p. 91-111
Series
Big Data, Artificial Intelligence and Data Analysis Set coordinated by Jacques Janssen ; 7
National Category
Computational Mathematics Probability Theory and Statistics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-56066DOI: 10.1002/9781119821588.ch5Scopus ID: 2-s2.0-85148063908ISBN: 978-1-78630-673-9 (print)OAI: oai:DiVA.org:mdh-56066DiVA, id: diva2:1599474
Funder
Sida - Swedish International Development Cooperation AgencyAvailable from: 2021-09-30 Created: 2021-09-30 Last updated: 2023-03-01Bibliographically approved

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Publisher's full textScopushttps://www.wiley.com/en-ag/Applied+Modeling+Techniques+and+Data+Analysis+1%3A+Computational+Data+Analysis+Methods+and+Tools-p-9781786306739

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Engström, ChristopherSilvestrov, Sergei

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