Contrastive analysis for scatterplot-based representations of dimensionality reduction

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorMarcílio-Jr, Wilson E.-
Autor(es): dc.creatorEler, Danilo M.-
Autor(es): dc.creatorGarcia, Rogério E.-
Data de aceite: dc.date.accessioned2025-08-21T20:58:39Z-
Data de disponibilização: dc.date.available2025-08-21T20:58:39Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.cag.2021.08.014-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/229131-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/229131-
Descrição: dc.descriptionCluster 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.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionFaculty of Sciences and Technology São Paulo State University (UNESP), Presidente Prudente-
Descrição: dc.descriptionFaculty of Sciences and Technology São Paulo State University (UNESP), Presidente Prudente-
Descrição: dc.descriptionFAPESP: #2018/17881-3-
Descrição: dc.descriptionFAPESP: #2018/25755-8-
Descrição: dc.descriptionCAPES: #88887.487331/2020-00-
Idioma: dc.languageen-
Relação: dc.relationComputers and Graphics (Pergamon)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectContrastive analysis-
Palavras-chave: dc.subjectDimensionality reduction-
Palavras-chave: dc.subjectVisual interpretation-
Título: dc.titleContrastive analysis for scatterplot-based representations of dimensionality reduction-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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