Polynomial asymptotic complexity of multiple-objective OLAP data cube compression

In this paper, we complement previous research results provided in [8], where the multiple-objective OLAP data cube compression paradigm has been introduced. This paradigm pursues the idea of compressing OLAP data cubes in the dependence of multiple requirements rather than only one, like in traditional approaches. Here, we provide a comprehensive description of algorithm computeMQHist, the main algorithm of the framework [8], which allows us to obtain compressed data cubes that adhere to the multiple-objective computational paradigm, and we prove that computeMQHist has a polynomial asymptotic complexity. © 2012 Springer-Verlag.