Parallel multi-level preference computation

  • Given a data set, a top-k Skyline query returns the k most interesting elements of the Skyline query based on some kind of user-defined preference. That means, sometimes not only the Pareto frontier is of interest, but also the stratum, the level, behind the Skyline to get exactly the top-k objects from a partially ordered set stratified into subsets of non-dominated tuples. In this paper, we extend the definition of top-k Skyline to form multi-level Skyline sets. Multi-level Skylines are a variant of top-k Skylines which do not stop after k tuples, but compute all Skyline levels. We present a parallel algorithm for multi-level Skyline computation on multi-core architectures and demonstrate through extensive experimentation on synthetic and real data sets that our algorithms can result in a significant performance advantage over existing techniques.

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Author:Markus EndresGND, Stefan Wohlfart
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Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2017-03)
Publishing Institution:Universität Augsburg
Release Date:2017/07/04
Tag:Parallel computation; Multi-level preference; Top-k; Skyline; Multi-core
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Datenbanken und Informationssysteme
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht mit Print on Demand