Retrieving accurate estimates to OLAP queries over uncertain and imprecise multidimensional data streams

Authors:
Alfredo Cuzzocrea
Affiliations:
ICAR, CNR and University of Calabria, Cosenza, Italy
Venue:
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Year:
2011

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Abstract

In this paper, we introduce a novel framework for estimating OLAP queries over uncertain and imprecise multidimensional data streams, along with three relevant research contributions: (i) a probabilistic data stream model, which describes both precise and imprecise multidimensional data stream readings in terms of nice confidence-interval-based Probability Distribution Functions (PDF); (ii) a possible-world semantics for uncertain and imprecise multidimensional data streams, which is based on an innovative data-driven approach that exploits "natural" features of OLAP data, such as the presence of clusters and high correlations; (iii) an innovative approach for providing theoretically-founded estimates to OLAP queries over uncertain and imprecise multidimensional data streams that exploits the well-recognized probabilistic estimators theory.