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BUC algorithm for iceberg cubes

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dc.contributor.author Nasr, George E.
dc.contributor.author Badr, Celine
dc.date.accessioned 2017-12-07T07:55:58Z
dc.date.available 2017-12-07T07:55:58Z
dc.date.copyright 2003 en_US
dc.identifier.uri http://hdl.handle.net/10725/6725
dc.description.abstract The Iceberg-Cube problem restricts the computation of the data cube to only those group-by partitions satisfying a minimum threshold condition defined on a specified measure. In this paper, we implement the Bottom-Up Computation (BUC) algorithm for computing Iceberg cubes and conduct a sensitivity analysis of BUC with respect to the probability density function of the data. The distributions under consideration are the Gaussian, Geometric, and Poisson distributions. The Uniform distribution is used as a basis for comparison. Results show that when the cube is sparse there is a correlation between the data distribution and the running time of the algorithm. In particular, BUC performs better on Uniform followed by Poisson, Gaussian and Geometric data. en_US
dc.language.iso en en_US
dc.title BUC algorithm for iceberg cubes en_US
dc.type Conference Paper / Proceeding en_US
dc.title.subtitle implementation and sensitivity en_US
dc.author.school SOE en_US
dc.author.idnumber 199390170 en_US
dc.author.department Electrical And Computer Engineering en_US
dc.description.embargo N/A en_US
dc.identifier.ctation Nasr, G. E., & Badr, C. (2003). BUC Algorithm for Iceberg Cubes: Implementation and Sensitivity Analysis. In FLAIRS Conference (pp. 255-260). en_US
dc.author.email genasr@lau.edu.lb en_US
dc.conference.date May 11-15, 2003 en_US
dc.conference.place St. Augustine, Florida, USA en_US
dc.conference.title 16th International FLAIRS Conference (FLAIRS-03) en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url http://www.aaai.org/Papers/FLAIRS/2003/Flairs03-050.pdf en_US
dc.author.affiliation Lebanese American University en_US


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