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Rate-Distortion Theory for Clustering in the Perceptual Space

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dc.contributor.author Bardera i Reig, Antoni
dc.contributor.author Bramon Feixas, Roger
dc.contributor.author Ruiz Altisent, Marc
dc.contributor.author Boada, Imma
dc.date.issued 2017-08-23
dc.identifier.issn 1099-4300
dc.identifier.uri http://hdl.handle.net/10256/14367
dc.description.abstract How to extract relevant information from large data sets has become a main challenge in data visualization. Clustering techniques that classify data into groups according to similarity metrics are a suitable strategy to tackle this problem. Generally, these techniques are applied in the data space as an independent step previous to visualization. In this paper, we propose clustering on the perceptual space by maximizing the mutual information between the original data and the final visualization. With this purpose, we present a new information-theoretic framework based on the rate-distortion theory that allows us to achieve a maximally compressed data with a minimal signal distortion. Using this framework, we propose a methodology to design a visualization process that minimizes the information loss during the clustering process. Three application examples of the proposed methodology in different visualization techniques such as scatterplot, parallel coordinates, and summary trees are presented cat
dc.description.sponsorship This work has been funded in part by grants from the Spanish Government (Nr. TIN2016- 75866-C3-3-R) and from the Catalan Government (Nr. 2014-SGR-1232) cat
dc.format.mimetype application/pdf cat
dc.language.iso eng cat
dc.publisher MDPI (Multidisciplinary Digital Publishing Institute) cat
dc.relation MINECO/PE 2016-2019/TIN2016- 75866-C3-3-R cat
dc.relation.isformatof Reproducció digital del document publicat a: https://doi.org/10.3390/e19090438 cat
dc.relation.ispartof Entropy, 2017, vol. 19, núm. 9, p. 438 cat
dc.relation.ispartofseries Articles publicats (D-IMA) cat
dc.rights Attribution 4.0 Spain *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/es/ *
dc.subject Visualització de la informació cat
dc.subject Information visualization cat
dc.subject Informació, Teoria de la cat
dc.subject Information theory cat
dc.title Rate-Distortion Theory for Clustering in the Perceptual Space cat
dc.type info:eu-repo/semantics/article cat
dc.rights.accessRights info:eu-repo/semantics/openAccess cat
dc.embargo.terms Cap cat
dc.type.version info:eu-repo/semantics/publishedVersion cat
dc.identifier.doi https://doi.org/10.3390/e19090438
dc.contributor.funder Ministerio de Economía y Competitividad (Espanya) cat

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Drets: Attribution 4.0 Spain

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