Estimated Distance Limited Betweenness Centrality Based on Estimated Betweenness and Approximate Betweenness Algorithms

We propose two kinds of estimated distance limited betweenness (k-BC) algorithm by combining k-BC with two estimated centrality betweenness centrality algorithms – publicly known as estimate betweenness and approximate betweenness. Proposed two algorithms are experimented on seven large real-world d...

Full description

Saved in:
Bibliographic Details
Published inJournal of Multimedia Information System Vol. 11; no. 3; pp. 185 - 192
Main Authors Gombojav, Gantulga, Purevsuren, Dalaijargal
Format Journal Article
LanguageEnglish
Published 한국멀티미디어학회 30.09.2024
Subjects
컴퓨터학
Online AccessGet full text

Cover

More Information
Summary:We propose two kinds of estimated distance limited betweenness (k-BC) algorithm by combining k-BC with two estimated centrality betweenness centrality algorithms – publicly known as estimate betweenness and approximate betweenness. Proposed two algorithms are experimented on seven large real-world datasets and compared against their original algorithms. Experimental result shows that both algorithms converge with k-BC and runs faster. Estimated k-BC based on estimated betweenness algorithm performs better than the other in respect to running time and similarity to k-BC. K-BC values are calculated at least 18−439 times faster by using these estimated k-BC algorithms. KCI Citation Count: 0
ISSN:2383-7632
2383-7632
DOI:10.33851/JMIS.2024.11.3.185