Distributed assessment of the closeness centrality ranking in complex networks
Proceedings of the Fourth Annual Workshop on Simplifying Complex Networks for Practitioners
Applications of machine learning to performance evaluation
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Quick detection of nodes with large degrees
WAW'12 Proceedings of the 9th international conference on Algorithms and Models for the Web Graph
Distributed Assessment of Network Centralities in Complex Social Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
DACCER: Distributed Assessment of the Closeness CEntrality Ranking in complex networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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The goal of this paper is to estimate the k most central nodes in a network through parsimonious sampling. Centrality determines the relative importance of a particular node within the network. Conventional measures of node centrality include degree, betweenness, and closeness.