Evaluation of a MCA-based approach to organize data cubes

Authors:
Riadh Ben Messaoud;Omar Boussaid;Sabine Loudcher Rabaséda
Affiliations:
University of Lyon 2, Bron Cedex, France;University of Lyon 2, Bron Cedex, France;University of Lyon 2, Bron Cedex, France
Venue:
Proceedings of the 14th ACM international conference on Information and knowledge management
Year:
2005

Citing 2
Cited 1

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A Multiple Correspondence Analysis to Organize Data Cubes

Proceedings of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006

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Abstract

In the OLAP context, exploration of huge and sparse data cubes is a tedious task that does not always lead to efficient results. We propose to use a Multiple Correspondence Analysis (MCA) in order to enhance data cube representations and make them more suitable for visualization and thus, easier to analyze. We also provide an original quality criterion to measure the relevance of the obtained data representations. Experimental results we led on real data samples have shown the interest and the efficiency of our approach.