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@InProceedings{MarcílioJrElerGarc:2017:ApPeLo,
               author = "Marc{\'{\i}}lio Jr, Wilson Est{\'e}cio and Eler, Danilo 
                         Medeiros and Garcia, Rog{\'e}rio Eduardo",
          affiliation = "{Universidade Estadual Paulista - UNESP} and {Universidade 
                         Estadual Paulista - UNESP} and {Universidade Estadual Paulista - 
                         UNESP}",
                title = "An approach to perform local analysis on multidimensional 
                         projection",
            booktitle = "Proceedings...",
                 year = "2017",
               editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and 
                         Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and 
                         Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba, 
                         Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo 
                         and Vital, Creto and Pagot, Christian Azambuja and Petronetto, 
                         Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
         organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "visualization, multidimensional projection, analysis.",
             abstract = "In the context of Visualization, Multidimensional Projection 
                         techniques are employed to show similarity relations among 
                         instances of a multidimensional dataset. Distinct projection 
                         techniques use different approaches to perform the dimensionality 
                         reduction and, consequently, different metrics are employed to 
                         assess projection quality according to similarity and structures 
                         preservation. Usually, quality measures are computed from the 
                         whole projection, what can impair a specific evaluation. This work 
                         presents a novel approach to perform evaluation on 
                         multidimensional projections, in which clusters of instances are 
                         selectively evaluated and compared to the whole projection. The 
                         proposed approach has shown to be effective on evaluating 
                         projections and it offers a way to apply techniques to enhance 
                         poor projected areas.",
  conference-location = "Niter{\'o}i, RJ",
      conference-year = "Oct. 17-20, 2017",
             language = "en",
           targetfile = "PID4959879.pdf",
        urlaccessdate = "2021, Jan. 26"
}


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