• Media type: E-Article; Electronic Conference Proceeding; Text
  • Title: K-Dominance in Multidimensional Data: Theory and Applications
  • Contributor: Schibler, Thomas [Author]; Suri, Subhash [Author]
  • imprint: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2017
  • Language: English
  • DOI: https://doi.org/10.4230/LIPIcs.ESA.2017.65
  • Keywords: skyline ; Dominance ; random vectors ; database search ; average case analysis
  • Origination:
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  • Description: We study the problem of k-dominance in a set of d-dimensional vectors, prove bounds on the number of maxima (skyline vectors), under both worst-case and average-case models, perform experimental evaluation using synthetic and real-world data, and explore an application of k-dominant skyline for extracting a small set of top-ranked vectors in high dimensions where the full skylines can be unmanageably large.
  • Access State: Open Access