Towards Reducing the Multidimensionality of OLAP Cubes Using the Evolutionary Algorithms and Factor Analysis Methods
Sami Naouali, Semeh Ben Salem · International Journal of Data Mining & Knowledge Management Process · 2016
Data Warehouses are structures with large amount of data collected from heterogeneous sources to be used in a decision support system.Data Warehouses analysis identifies hidden patterns initially unexpected which analysis requires great memory and computation cost.Data reduction methods were proposed to make this analysis easier.In this paper, we present a hybrid approach based on Genetic Algorithms (GA) as Evolutionary Algorithms and the Multiple Correspondence Analysis (MCA) as Analysis Factor Methods to conduct this reduction.Our approach identifies reduced subset of dimensions p' from the initial subset p where p'