@InProceedings{HolandaRomBotZanBor:2022:FoDaAn,
               author = "Holanda, Maria Eduarda M. de and Rom{\~a}o, Bernardo and Botelho, 
                         Raquel Braz Assun{\c{c}}{\~a}o and Zandonadi, Renata Puppin and 
                         Borges, Vin{\'{\i}}cius R. P.",
          affiliation = "{Universidade de Bras{\'{\i}}lia} and {Universidade de 
                         Bras{\'{\i}}lia} and {Universidade de Bras{\'{\i}}lia} and 
                         {Universidade de Bras{\'{\i}}lia} and {Universidade de 
                         Bras{\'{\i}}lia}",
                title = "Food Data Analysis using Multidimensional Visualizations based on 
                         Point Placement",
            booktitle = "Proceedings...",
                 year = "2022",
         organization = "Conference on Graphics, Patterns and Images, 35. (SIBGRAPI)",
             keywords = "food composition data, data visualization, visual data mining, 
                         point placement strategies.",
             abstract = "Food data comprise records regarding nutrients, ingredients, 
                         amounts of different vitamins and minerals that can be found in 
                         foods. The wide variety of food products that can be stored in 
                         large datasets makes the traditional analysis tasks unfeasible and 
                         time-consuming when conducted manually by the dietitians and 
                         related professionals. This paper describes a method for 
                         visualizing food data using point placement strategies to support 
                         specialists in tasks related to determining similar food products 
                         that can be replaced in specific diets. The proposed method 
                         generates a structured representation for food data to be used as 
                         input to some state-of-the-art and recent visualizations, such as 
                         PCA, t-SNE, UMAP and TriMap. Experiments were conducted to assess 
                         the quality of visualizations and the results reported that the 
                         nonlinear visualizations presented satisfactory discriminability 
                         regarding some food categories and better preservation of the data 
                         patterns. A case study based on a visual exploration process was 
                         also conducted and demonstrates the specialist successfully 
                         finding substitute food products for planning a vegan diet plan.",
  conference-location = "Natal, RN",
      conference-year = "24-27 Oct. 2022",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/47RJ2EE",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/47RJ2EE",
           targetfile = "wuw2022_camera_ready_correct.pdf",
        urlaccessdate = "2024, May 01"
}