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Issue No.11 - Nov. (2013 vol.19)
pp: 1833-1845
S. Lafon , Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
F. Bouali , Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
C. Guinot , Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
G. Venturini , Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
In this paper, we propose a new method for the visual reorganization of online analytical processing (OLAP) cubes that aims at improving their visualization. Our method addresses dimensions with hierarchically organized members. It uses a genetic algorithm that reorganizes k-ary trees. Genetic operators perform permutations of subtrees to optimize a visual homogeneity function. We propose several ways to reorganize an OLAP cube depending on which set of members is selected for the reorganization: all of the members, only the displayed members, or the members at a given level (level by level approach). The results that are evaluated by using optimization criteria show that our algorithm has a reliable performance even when it is limited to 1 minute runs. Our algorithm was integrated in an interactive 3D interface for OLAP. A user study was conducted to evaluate our approach with users. The results highlight the usefulness of reorganization in two OLAP tasks.
Visualization, Genetic algorithms, Three-dimensional displays, Data visualization, Genetics, Sociology, Statistics,interactive knowledge discovery, Dimension reorganization, visual OLAP
S. Lafon, F. Bouali, C. Guinot, G. Venturini, "Hierarchical Reorganization of Dimensions in OLAP Visualizations", IEEE Transactions on Visualization & Computer Graphics, vol.19, no. 11, pp. 1833-1845, Nov. 2013, doi:10.1109/TVCG.2013.93
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