Multidimensional databases are commonly used for decision making in the context of data warehouses. Considering the multidimensional model, data are presented as hypercubes organized according to several dimensions. However, in general, hypercubes have more than three dimensions and contain a huge amount of data, and so cannot be easily visualized. In this paper, we show that data cubes can be visualized as images by building blocks that contain mostly the same value. Blocks are built up using an APriori-like algorithm and each block is considered as a set of pixels which colors depend on the corresponding value. The key point of our approach is to set how to display a given block according to its corresponding value while taking into account that blocks may overlap. In this paper, we address this issue based on the Pixelization paradigm. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Choong, Y. W., Laurent, A., & Laurent, D. (2007). Pixelizing data cubes: A block-based approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4370 LNCS, pp. 63–76). Springer Verlag. https://doi.org/10.1007/978-3-540-71027-1_7
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