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Pixelizing Data Cubes: A Block-Based Approach.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Lévy, Pierre P
Le Grand, Bénédicte
Poulet, François
Soto, Michel
Darago, Laszlo
Source :
Pixelization Paradigm; 2007, p63-76, 14p
Publication Year :
2007

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540710264
Database :
Complementary Index
Journal :
Pixelization Paradigm
Publication Type :
Book
Accession number :
33094774
Full Text :
https://doi.org/10.1007/978-3-540-71027-1_7