@InProceedings{OnoSiCoPaPaNo:2015:ViExMu,
               author = "Ono, Jorge Henrique Piazentin and Sikansi, Fabio and Corr{\^e}a, 
                         D{\'e}bora Cristina and Paulovich, Fernando Vieira and Paiva, 
                         Afonso and Nonato, Luis Gustavo",
          affiliation = "{ICMC - USP} and {ICMC - USP} and {ICMC - USP} and {ICMC - USP} 
                         and {ICMC - USP} and {ICMC - USP}",
                title = "Concentric RadViz: Visual Exploration of Multi-Task 
                         Classification",
            booktitle = "Proceedings...",
                 year = "2015",
               editor = "Papa, Jo{\~a}o Paulo and Sander, Pedro Vieira and Marroquim, 
                         Ricardo Guerra and Farrell, Ryan",
         organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "RadViz, Multi-task classification, Information Visualization.",
             abstract = "The discovery of patterns in large data collections is a difficult 
                         task. Visualization and machine learning techniques have emerged 
                         as a way to facilitate data analysis, providing tools to uncover 
                         relevant patterns from the data. This paper presents Concentric 
                         RadViz, a general purpose class visualization system that takes 
                         into account multi-class, multi-label and multi-task classifiers. 
                         Concentric RadViz uses a force attenuation scheme, which minimizes 
                         cluttering and ambiguity in the visual layout. In~addition, the 
                         user can add concentric circles to the layout in order to 
                         represent classification tasks. Our validation results and the 
                         application of Concentric RadViz for two real collections suggest 
                         that this tool can reveal important data patterns and relations. 
                         In our application, the user can interact with the visualization 
                         by selecting regions of interest according to specific criteria 
                         and changing projection parameters.",
  conference-location = "Salvador, BA, Brazil",
      conference-year = "26-29 Aug. 2015",
                  doi = "10.1109/SIBGRAPI.2015.38",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2015.38",
             language = "en",
                  ibi = "8JMKD3MGPBW34M/3JMJNL8",
                  url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3JMJNL8",
           targetfile = "PID3770563.pdf",
        urlaccessdate = "2024, May 02"
}