An Adaptive Sampling Algorithm for the Top- K Group Betweenness Centrality

Betweenness centrality is one of the key centrality measures in many applications including community detections in biological networks, vulnerability detections in communication networks, misinformation filtering in social networks, etc. The top- K group betweenness centrality problem is to find a...

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Bibliographic Details

Published in:	Data engineering pp. 170 - 182
Main Authors:	Xu, Wenzheng, Mao, Honglin, Shao, Heng, Liang, Weifa, Peng, Jian, Huang, Wen, Xu, Zichuan, Zhou, Pan, Yu, Jeffrey Xu
Format:	Conference Proceeding
Language:	English
Published:	IEEE 19.05.2025
Subjects:	Approximation algorithms Biology Communication networks Data engineering Fake news Filtering Group betweenness centrality randomized algorithms Social networking (online)
ISSN:	2375-026X
Online Access:	Get full text
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