Contrastive analysis for scatterplot-based representations of dimensionality reduction

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dc.contributor.authorMarcílio-Jr, Wilson E. [UNESP]
dc.contributor.authorEler, Danilo M. [UNESP]
dc.contributor.authorGarcia, Rogério E. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-29T08:30:39Z
dc.date.available2022-04-29T08:30:39Z
dc.date.issued2021-01-01
dc.description.abstractCluster interpretation after dimensionality reduction (DR) is a ubiquitous part of exploring multidimensional datasets. DR results are frequently represented by scatterplots, where spatial proximity encodes similarity among data samples. In the literature, techniques support the understanding of scatterplots’ organization by visualizing the importance of the features for cluster definition with layout enrichment strategies. However, current approaches usually focus on global information, hampering the analysis whenever the focus is to understand the differences among clusters. Thus, this paper introduces a methodology to visually explore DR results and interpret clusters’ formation based on contrastive analysis. We also introduce a bipartite graph to visually interpret and explore the relationship between the statistical variables employed to understand how the data features influence cluster formation. Our approach is demonstrated through case studies, in which we explore two document collections related to news articles and tweets about COVID-19 symptoms. Finally, we evaluate our approach through quantitative results to demonstrate its robustness to support multidimensional analysis.en
dc.description.affiliationFaculty of Sciences and Technology São Paulo State University (UNESP), Presidente Prudente
dc.description.affiliationUnespFaculty of Sciences and Technology São Paulo State University (UNESP), Presidente Prudente
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdFAPESP: #2018/17881-3
dc.description.sponsorshipIdFAPESP: #2018/25755-8
dc.description.sponsorshipIdCAPES: #88887.487331/2020-00
dc.identifierhttp://dx.doi.org/10.1016/j.cag.2021.08.014
dc.identifier.citationComputers and Graphics (Pergamon).
dc.identifier.doi10.1016/j.cag.2021.08.014
dc.identifier.issn0097-8493
dc.identifier.scopus2-s2.0-85109949819
dc.identifier.urihttp://hdl.handle.net/11449/229131
dc.language.isoeng
dc.relation.ispartofComputers and Graphics (Pergamon)
dc.sourceScopus
dc.subjectContrastive analysis
dc.subjectDimensionality reduction
dc.subjectVisual interpretation
dc.titleContrastive analysis for scatterplot-based representations of dimensionality reductionen
dc.typeArtigo
unesp.author.orcid0000-0002-8580-2779[1]
unesp.author.orcid0000-0002-9493-145X[2]
unesp.departmentEstatística - FCTpt

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Presidente Prudente - FCT - Faculdade de Ciências e Tecnologia