ProxiLens: Interactive Exploration of High-Dimensional Data using Projections

Heulot, N.; Aupetit, M.; Fekete, J-D.

ProxiLens: Interactive Exploration of High-Dimensional Data using Projections

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proxilens_eurovis2013.avi (4.93 MB)

Date

2013

Authors

Heulot, N.
Aupetit, M.
Fekete, J-D.

Publisher

The Eurographics Association

Abstract

As dimensionality increases, analysts are faced with difficult problems to make sense of their data. In exploratory data analysis, multidimensional scaling projections can help analyst to discover patterns by identifying outliers and enabling visual clustering. However to exploit these projections, artifacts and interpretation issues must be overcome. We present ProxiLens, a semantic lens which helps exploring data interactively. The analyst becomes aware of the artifacts navigating in a continuous way through the 2D projection in order to cluster and analyze data. We demonstrate the applicability of our technique for visual clustering on synthetic and real data sets.

        @inproceedings{:10.2312/PE.VAMP.VAMP2013.011-015
,
booktitle = {EuroVis Workshop on Visual Analytics using Multidimensional Projections
},
editor = {M. Aupetit and L. van der Maaten
},
title = {{ProxiLens: Interactive Exploration of High-Dimensional Data using Projections
}},
author = {Heulot, N. and 
Aupetit, M. and 
Fekete, J-D.
},
year = {2013
},
publisher = {The Eurographics Association
},
ISBN = {978-3-905674-53-8
},
DOI = {/10.2312/PE.VAMP.VAMP2013.011-015
}
}