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dc.contributor.authorShi, Quan
dc.contributor.authorXiao, Yanghua
dc.contributor.authorBessis, Nik
dc.contributor.authorLu, Yiqi
dc.contributor.authorChen, Yaoliang
dc.contributor.authorHill, Richard
dc.date.accessioned2012-05-21T11:42:44Z
dc.date.available2012-05-21T11:42:44Z
dc.date.issued2012-01
dc.identifier.citationOptimizing trees: a case for validating the maturity of network of practices 2012, 63 (2):427 Computers & Mathematics with Applicationsen
dc.identifier.issn08981221
dc.identifier.issn08981221
dc.identifier.doi10.1016/j.camwa.2011.07.060
dc.description.abstractOf 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.
dc.publisherElsevieren
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0898122111006353en
dc.rightsArchived with thanks to Computers & Mathematics with Applicationsen
dc.subjectK2 treeen
dc.subjectStorage optimizationen
dc.subjectDFS codeen
dc.subjectCompression algorithmen
dc.subjectNetwork of practicesen
dc.titleOptimizing K2 trees: a case for validating the maturity of network of practices
dc.typeArticleen
dc.contributor.departmentNantong University, Nantong, China, School of Computer Science and Technologyen
dc.contributor.departmentFudan University, Shanghai, China, School of Computer Scienceen
dc.contributor.departmentUniversity of Derby, School of Computing and Mathematicsen
dc.identifier.journalComputers & Mathematics with Applicationsen
html.description.abstractOf 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.


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