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dc.contributor.authorRiesen, Kaspar
dc.contributor.authorDornberger, Rolf
dc.contributor.authorBunke, Horst
dc.date.accessioned2015-10-05T06:31:44Z
dc.date.available2015-10-05T06:31:44Z
dc.date.issued2014
dc.identifier.isbnISBN 978-1-4799-3244-3
dc.identifier.urihttp://hdl.handle.net/11654/8223
dc.description.abstractOne of the major tasks in many applications in the field of document analysis is the computation of dissimilarities between two or more objects from a given problem domain. Hence, employing graphs as representation formalism evokes the need for powerful, fast and flexible graph based dissimilarity models. Graph edit distance is powerful and applicable to any kind of graphs but suffers from its high computational complexity. Recently, however, a novel framework for graph edit distance approximation has been introduced. While the run time of this novel procedure is very convincing, the precision of the approximated graph distances is dissatisfying in some cases. The present paper introduces a generalized version of the existing approximation framework using an iterative bipartite procedure. With empirical investigations on three real world data sets we show that our extension substantially improves the accuracy of the approximations while the run time is increased only linearly with the number of additional iterations.
dc.language.isoen
dc.relation.ispartofDocument Analysis Systems
dc.relation.ispartofseriesIEEE Computer Society 2014;
dc.accessRightsAnonymous
dc.subject.ddc330 - Wirtschaftde
dc.titleIterative Bipartite Graph Edit Distance Approximation.
dc.type04 - Beitrag Sammelband oder Konferenzschrift
dc.spatialTours
dc.audienceScience
fhnw.publicationStatePublished
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.InventedHereYes
fhnw.PublishedSwitzerlandNo
fhnw.pagination724-731
fhnw.IsStudentsWorkno


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