Assortative partitions of complete graphs

Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/27396

DC Field	Value	Language
dc.contributor.author	Zlatanova, Magdalena	en_US
dc.date.accessioned	2023-08-15T08:25:22Z	-
dc.date.available	2023-08-15T08:25:22Z	-
dc.date.issued	2023-07	-
dc.identifier.uri	http://hdl.handle.net/20.500.12188/27396	-
dc.description.abstract	This paper studies the problem of assortative partitions of complete graphs. Assortativity is a measure of the similarity of each node to its neighborhood. The results from numerical simulations suggest that for this class of graphs the assortative partitioning problem becomes more difficult as we increase the assortativity threshold. We observe a significant difference in the performance of the Gradient Descent algorithm when our assortativity threshold is set to 4 instead of 2. This numerically supports the hypothesis that the problem becomes more difficult.	en_US
dc.publisher	Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia	en_US
dc.relation.ispartofseries	CIIT 2023 papers;21;	-
dc.subject	Combinatorial optimization, NP class, complete graphs, graph partitioning, statistical physics	en_US
dc.title	Assortative partitions of complete graphs	en_US
dc.type	Proceeding article	en_US
dc.relation.conference	20th International Conference on Informatics and Information Technologies - CIIT 2023	en_US
item.grantfulltext	open	-
item.fulltext	With Fulltext	-
Appears in Collections:	Faculty of Computer Science and Engineering: Conference papers

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