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.
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© 2011 Springer-Verlag Berlin Heidelberg
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Cuzzocrea, A. (2011). Retrieving Accurate Estimates to OLAP Queries over Uncertain and Imprecise Multidimensional Data Streams. In: Bayard Cushing, J., French, J., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2011. Lecture Notes in Computer Science, vol 6809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22351-8_43
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DOI: https://doi.org/10.1007/978-3-642-22351-8_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22350-1
Online ISBN: 978-3-642-22351-8
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