Random dot product graphs: a flexible model for complex networks

dc.contributor.advisor Mihail, Milena
dc.contributor.author Young, Stephen J. en_US
dc.contributor.committeeMember Lu, Linyuan
dc.contributor.committeeMember Sokol, Joel
dc.contributor.committeeMember Tetali, Prasad
dc.contributor.committeeMember Trotter, Tom
dc.contributor.department Mathematics en_US
dc.date.accessioned 2009-01-22T15:44:55Z
dc.date.available 2009-01-22T15:44:55Z
dc.date.issued 2008-11-17 en_US
dc.description.abstract Over the last twenty years, as biological, technological, and social net- works have risen in prominence and importance, the study of complex networks has attracted researchers from a wide range of fields. As a result, there is a large and diverse body of literature concerning the properties and development of models for complex networks. However, many of the models that have been previously developed, although quite successful at capturing many observed properties of complex networks, have failed to capture the fundamental semantics of the networks. In this thesis, we propose a robust and general model for complex networks that incorporates at a fundamental level semantic information. We show that for a large range of average degrees and with a suitable choice of parameters, this model exhibits the three hallmark properties of complex networks: small diameter, clustering, and skewed degree distribution. Additionally, we provide a structural interpretation of assortativity and apply this strucutral assortativity to the random dot product graph model. We also extend the results of Chung, Lu, and Vu on the spectral gap of the expected degree sequence model to a general class of random graph models with independent edges. We apply this result to the recently developed Stochastic Kronecker graph model of Leskovec, Chakrabarti, Kleinberg, and Faloutsos. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/26548
dc.publisher Georgia Institute of Technology en_US
dc.subject Comlex networks en_US
dc.subject Random graphs en_US
dc.subject Power-law en_US
dc.subject Clustering en_US
dc.subject Assortativity en_US
dc.subject Spectral gap en_US
dc.subject Conductance en_US
dc.subject.lcsh Cluster analysis
dc.subject.lcsh Mathematical statistics
dc.subject.lcsh Random graphs
dc.title Random dot product graphs: a flexible model for complex networks en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.corporatename College of Sciences
local.contributor.corporatename School of Mathematics
relation.isOrgUnitOfPublication 85042be6-2d68-4e07-b384-e1f908fae48a
relation.isOrgUnitOfPublication 84e5d930-8c17-4e24-96cc-63f5ab63da69
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