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iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
(Elsevier Ltd, 2016)
Star Coordinates is an important visualization method able to reveal patterns and groups from multidimensional data while still showing the impact of data attributes in the formation of such patterns and groups. Despite ...
An incremental space to visualize dynamic data sets
(SPRINGER, 2010)
In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We have developed an inherently incremental technique (incBoard) that maintains a coherent disposition of ...
HiPP: A Novel Hierarchical Point Placement Strategy and its Application to the Exploration of Document Collections
(IEEE COMPUTER SOC, 2008)
Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for ...
Dimensionality reduction for visualization of normal and pathological speech data
(Elsevier, 2009-07)
For an adequate analysis of pathological speech signals, a sizeable number of parameters is required, such as those related to jitter, shimmer and noise content. Often this kind of high-dimensional signal representation ...
Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data
(WILEY-BLACKWELLHOBOKEN, 2012)
Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve ...
Visual analysis of dimensionality reduction quality for parameterized projections
(Pergamon-Elsevier ScienceOxford, 2014-06)
In recent years, many dimensionality reduction (DR) algorithms have been proposed for visual analysis of multidimensional data. Given a set of n-dimensional observations, such algorithms create a 2D or 3D projection thereof ...
LoCH: a neighborhood-based multidimensional projection technique for high-dimensional sparse spaces
(ElsevierAmsterdam, 2015-02)
On the last few years multidimensional projection techniques have advanced towards defining faster and user-centered approaches. However,most of existing methods are designed as generic tools without considering particular ...
Semi-Supervised Dimensionality Reduction based on Partial Least Squares for Visual Analysis of High Dimensional Data
(Wiley-BlackwellHoboken, 2012)
Two-Phase Mapping for Projecting Massive Data Sets
(IEEE COMPUTER SOC, 2010)
Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra ...
Visualization of music collections based on structural content similarity
(Fundação Getulio Vargas - FGVEscola de Matemática Aplicada - EMApIEEE Computer SocietyRio de Janeiro, 2014-08)
Users interact a lot with their personal music collections, typically using standard text-based interfaces that offer constrained functionalities based on assigned metadata or tags. Alternative visual interfaces have been ...