dimensionality reduction – Valcri https://valcri.org VALCRI is a European Union project Thu, 16 Feb 2017 09:44:28 +0000 en-US hourly 1 https://wordpress.org/?v=5.2.2 White Paper WP-2017-011: Applying Visual Interactive Dimensionality Reduction to Criminal Intelligence Analysis https://euprojectvalcri.org/publications/white-paper-applying-visual-interactive-dimensionality-reduction-to-criminal-intelligence-analysis/ Fri, 13 Jan 2017 11:04:45 +0000 https://euprojectvalcri.org/?p=1520 ...]]> VALCRI provides a challenging and overwhelming high-dimensional dataset that comprises of hundreds of extracted semantic features in addition to the usual spatiotemporal information or metadata. To overcome the curse of dimensionality and to generate low-dimensional representations of these semantic features we apply interactive high-dimensional data analysis techniques with the goal of obtaining clusters of similar crime reports. However, it is still a challenge for crime analysts to make sense of the results and to provide useful interactive feedback to the system. Therefore, we provide several tightly integrated interactive visualizations that allow the analysts to identify clusters of similar crimes from different perspectives and interactively focus their analysis on features or crime records of particular interest.

Keywords

Criminal Intelligence, High-Dimensional Data Analysis, Feature Extraction, Dimensionality Reduction, Visual Analytics

VALCRI WHITE PAPER SERIES

VALCRI-WP-2017-011 Interactive Visual Dimension Reduction

]]> Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis. https://euprojectvalcri.org/publications/visual-interaction-with-dimensionality-reduction-a-structured-literature-analysis/ Wed, 28 Sep 2016 08:44:25 +0000 https://euprojectvalcri.org/?p=1411 ...]]>

D. Sacha, L. Zhang, M. Sedlmair, J. A. Lee, J. Peltonen, D. Weiskopf, S. C. North and D. A. Keim. Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis.
IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Visual Analytics Science and Technology), DOI: 10.1109/TVCG.2016.2598495, 2016.
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