Graph visualization with latent variable models

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Nybo, Kristian
dc.contributor.author Parkkinen, Juuso
dc.contributor.author Kaski, Samuel
dc.date.accessioned 2011-11-28T13:23:48Z
dc.date.available 2011-11-28T13:23:48Z
dc.date.issued 2009
dc.identifier.isbn 978-952-248-095-5
dc.identifier.issn 1797-5042
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/899
dc.description.abstract Large graph layout design by choosing locations for the vertices on the plane, such that the drawn set of edges is understandable, is a tough problem. The goal is ill-defined and usually both optimization and evaluation criteria are only very indirectly related to the goal. We suggest a new and surprisingly effective visualization principle: Position nodes such that nearby nodes have similar link distributions. Since their edges are similar by definition, the edges will become visually bundled and do not interfere. For the definition of similarity we use latent variable models which incorporate the user's assumption of what is important in the graph, and given the similarity construct the visualization with a suitable nonlinear projection method capable of maximizing the precision of the display. We finally show that the method outperforms alternative graph visualization methods empirically, and that at least in the special case of clustered data the method is able to properly abstract and visualize the links. en
dc.format.extent 15
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Helsinki University of Technology en
dc.publisher Teknillinen korkeakoulu fi
dc.relation.ispartofseries TKK reports in information and computer science en
dc.relation.ispartofseries 20 en
dc.subject.other Computer science en
dc.title Graph visualization with latent variable models en
dc.type D4 Julkaistu kehittämis- tai tutkimusraportti taikka -selvitys fi
dc.contributor.school Faculty of Information and Natural Sciences en
dc.contributor.school Informaatio- ja luonnontieteiden tiedekunta fi
dc.contributor.department Department of Information and Computer Science en
dc.contributor.department Tietojenkäsittelytieteen laitos fi
dc.subject.keyword graph clustering en
dc.subject.keyword graph visualization en
dc.subject.keyword latent variable model en
dc.identifier.urn urn:nbn:fi:tkk-013045
dc.type.dcmitype text en


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