Including the user in the knowledge discovery loop: interactive itemset-driven rule extraction
Proceedings of the 2008 ACM symposium on Applied computing
Incremental board: a grid-based space for visualizing dynamic data sets
Proceedings of the 2009 ACM symposium on Applied Computing
RankVisu: Mapping from the neighborhood network
Neurocomputing
An incremental space to visualize dynamic data sets
Multimedia Tools and Applications
Visualization of text streams: a survey
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Efficiency issues of evolutionary k-means
Applied Soft Computing
Murvis: enhancing the visualization of multiple response survey
Proceedings of the 15th WSEAS international conference on Computers
EASE'10 Proceedings of the 14th international conference on Evaluation and Assessment in Software Engineering
Time-aware visualization of document collections
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Structural decomposition trees
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Text mapping: Visualising unstructured, structured, and time-based text collections
Intelligent Decision Technologies - Knowledge Visualization
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Multidimensional projections map data points, defined in a high-dimensional data space, into a 1D, 2D or 3D representation space. Such a mapping may be typically achieved with dimensional reduction, clustering, or force directed point placement. Projections can be displayed and navigated by data analysts by means of visual representations, which may vary from points on a plane to graphs, surfaces or volumes. Typically, projections strive to preserve distance relationships amongst data points, as defined in the original space. Information loss is inevitable and the projection approach defines the extent to which the distance preserving goal is attained. We introduce PEx -- the Projection Explorer -- a visualization tool for mapping and exploration of high-dimensional data via projections. A set of examples -- on both structured (table) and unstructured (text) data -- illustrate how projection based visualizations, coupled with appropriate exploration tools, offer a flexible set-up for multidimensional data exploration. The projections in PEx handle relatively large data sets at a computational cost adequate to user interaction.