Section: Application Domains

Decision Support Systems

Datacubes are an intuitive interface allowing users to mine their data by selecting subsets of dimensions, drilling down and rolling up through dimensions hierarchies and by constraining some dimensions values. In order to optimize this navigation, the best solution would be to precompute all possible query results. However, this is unfeasible in practice. Hence one has to select the “most beneficial" part to precompute and materialize. Traditionally, this problem has been modeled as a query execution time minimization under storage space hard constraint. We have proposed to revisit this problem by considering query performance as being the hard constraint whilst minimizing the storage space. Due to the hardness of this problem, we proposed approximate solutions. For this purpose, we used, among others, the concept of border which is encountered in several data mining applications. We developed a general parallel algorithm for computing such borders with performance guarantees which is quite easily adaptable to the case where the data are distributed. This algorithm has been implemented and the extensive experiments confirmed the theoretical results.