Optimizing K2 trees: a case for validating the maturity of network of practices
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Affiliation
Nantong University, Nantong, China, School of Computer Science and TechnologyFudan University, Shanghai, China, School of Computer Science
University of Derby, School of Computing and Mathematics
Issue Date
2012-01
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Of late there has been considerable interest in the efficient and effective storage of large-scale network graphs, such as those within the domains of social networks, web and virtual communities. The representation of these data graphs is a complex and challenging task and arises as a result of the inherent structural and dynamic properties of a community network, whereby naturally occurring churn can severely affect the ability to optimize the network structure. Since the organization of the network will change over time, we consider how an established method for storing large data graphs (K^2 tree) can be augmented and then utilized as an indicator of the relative maturity of a community network. Within this context, we present an algorithm and a series of experimental results upon both real and simulated networks, illustrating that the compression effectiveness reduces as the community network structure becomes more dynamic. It is for this reason we highlight a notable opportunity to explore the relevance between the K^2 tree optimization factor with the maturity level of the network community concerned.Citation
Optimizing trees: a case for validating the maturity of network of practices 2012, 63 (2):427 Computers & Mathematics with ApplicationsPublisher
ElsevierJournal
Computers & Mathematics with ApplicationsDOI
10.1016/j.camwa.2011.07.060Additional Links
http://linkinghub.elsevier.com/retrieve/pii/S0898122111006353Type
ArticleISSN
0898122108981221
ae974a485f413a2113503eed53cd6c53
10.1016/j.camwa.2011.07.060