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Conference papers
ProxiLens: Interactive Exploration of High-Dimensional Data using Projections
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.
Cited literature [18 references]
https://hal.inria.fr/hal-01523025
Contributor : Jean-Daniel Fekete Connect in order to contact the contributor
Submitted on : Sunday, October 8, 2017 - 9:26:20 AM
Last modification on : Tuesday, December 14, 2021 - 3:53:19 AM
Long-term archiving on: : Tuesday, January 9, 2018 - 12:32:29 PM
Contributor : Jean-Daniel Fekete Connect in order to contact the contributor
Submitted on : Sunday, October 8, 2017 - 9:26:20 AM
Last modification on : Tuesday, December 14, 2021 - 3:53:19 AM
Long-term archiving on: : Tuesday, January 9, 2018 - 12:32:29 PM
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proxilens.pdf
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