Estimating Clustering Coefficient via Random Walk on MapReduce

Clustering coefficient plays an important role in many real-world applications, such as social network analysis and community mining. However, it is expensive to compute exact clustering coefficient for large networks. In many real-world applications, estimating clustering coefficient via random wal...

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Veröffentlicht in:	2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS) S. 493 - 500
Hauptverfasser:	Liao, Qun, Yang, Yulu
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2017
Schlagworte:	Approximation algorithms Clustering algorithms clustering coefficient Control engineering distributed algorithm Distributed algorithms Distributed computing graph analysis MapReduce Merging random walk Social network services
ISSN:	1521-9097
Online-Zugang:	Volltext
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