Tracking local communities in streaming graphs with a dynamic algorithm

A variety of massive datasets, such as social networks and biological data, are represented as graphs that reveal underlying connections, trends, and anomalies. Community detection is the task of discovering dense groups of vertices in a graph. Its one specific form is seed set expansion, which find...

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Vydané v:	Social network analysis and mining Ročník 6; číslo 1; s. 65
Hlavní autori:	Zakrzewska, Anita, Bader, David A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Vienna Springer Vienna 01.12.2016 Springer Nature B.V
Predmet:	Algorithms Apexes Applications of Graph Theory and Complex Networks Community Computation Computer Science Data Data Mining and Knowledge Discovery Economics Game Theory Graph theory Graphical representations Graphs Greedy algorithms Humanities Latency Law Massive data points Methodology of the Social Sciences Methods Modularity Original Article Seeds Social and Behav. Sciences Social networks Statistics for Social Sciences Tracking Static Algorithm Dynamic Algorithm Fitness Score Community Detection Batch Size
ISSN:	1869-5450, 1869-5469
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