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Conference Papers Year : 2008

Novel Labeling Strategies for Hierarchical Representation of Multidimensional Data Analysis Results

Abstract

Hyperbolic visualization represents a useful tool for the interpretation of complex data analysis results, whenever it can be combined with efficient labeling strategies. In this paper, we firstly present a new approach combining original hypertree construction techniques for multidimensional clustering results visualization with novel cluster labeling techniques based on the use of cluster content evaluation criteria, like the F-measure on cluster properties. The first part of the paper briefly presents the cluster hypertree construction principle. The main part of the paper focuses on the presentation of the labeling techniques. It illustrates that the scope of the proposed techniques can be extended from single cluster labeling to labeling of hierarchical structures, like hypertrees. Finally, using specific evaluation criteria, we show the better efficiency of the proposed methods, as compared to usual labeling methods, both for single cluster labeling and for hierarchical labeling. The experimental context of the paper is a bibliographic database of 2127 PASCAL references related to the geological domain.
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Dates and versions

inria-00337304 , version 1 (06-11-2008)

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  • HAL Id : inria-00337304 , version 1

Cite

Jean-Charles Lamirel, Anh Phuong Ta, Mohammed Attik. Novel Labeling Strategies for Hierarchical Representation of Multidimensional Data Analysis Results. AIA - IASTED, Feb 2008, Innbruck, Austria. ⟨inria-00337304⟩
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