Novel Labeling Strategies for Hierarchical Representation of Multidimensional Data Analysis Results
| Autor: | Lamirel, Jean-Charles, Phuong Ta, Anh, Attik, Mohammed |
|---|---|
| Přispěvatelé: | Natural Language Processing: representation, inference and semantics (TALARIS), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP), Neuromimetic intelligence (CORTEX), INRIA Lorraine, Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: | |
| Zdroj: | AIA-IASTED AIA-IASTED, Feb 2008, Innbruck, Austria |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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