Evaluation of a MCA-based approach to organize data cubes
Riadh Ben Messaoud, Omar Boussaïd, Sabine Loudcher · 2005
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.