Graph clustering

dc.contributor.degreegrantinginstitution	Athens University of Economics and Business, Department of Statistics	en
dc.contributor.opponent	Psarakis, Stelios	en
dc.contributor.opponent	Tsekrekos, Andrianos	en
dc.contributor.thesisadvisor	Yannacopoulos, Athanasios	en
dc.creator	Lamprinakou, Stamatina	en
dc.creator	Λαμπρινάκου, Σταματίνα	el
dc.date.accessioned	2018-07-18	*
dc.date.available	2025-03-26T19:45:52Z
dc.date.issued	2018-07-10	*
dc.date.issuedoriginal	07/10/2018	*
dc.date.submitted	2018-07-18 11:35:07
dc.description.abstract	The goal of the thesis is the study of graphs emphasizing on laplacian matrices and spectral clustering. The first chapter constitutes an introduction to graphs. In the second chapter we introduce laplacian matrices, while in the third chapter we represent some of the most ubiquitous spectral clustering algorithms. The application of the thesis is clustering of bond yield data. In the appendix we cite some code for the clustering of bond yield data.	en
dc.embargo.expire	2018-07-18 11:35:07
dc.embargo.rule	Open access
dc.format.extent	109 p.
dc.identifier	http://www.pyxida.aueb.gr/index.php?op=view_object&object_id=6401
dc.identifier.uri	https://pyxida.aueb.gr/handle/123456789/7714
dc.identifier.uri	https://doi.org/10.26219/heal.aueb.6509
dc.language	en
dc.rights	CC BY: Attribution alone 4.0
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Graphs	el
dc.subject	Laplacian matrices	el
dc.subject	Spectral clustering	el
dc.title	Graph clustering	en
dc.type	Text

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