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Approximately Dominating Representatives

  • Vladlen Koltun
  • Christos H. Papadimitriou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3363)

Abstract

We propose and investigate from the algorithmic standpoint a novel form of fuzzy query called approximately dominating representatives or ADRs. The ADRs of a multidimensional point set consist of a few points guaranteed to contain an approximate optimum of any monotone Lipschitz continuous combining function of the dimensions. ADRs can be computed by appropriately post-processing Pareto, or “skyline,” queries [14,1]. We show that the problem of minimizing the number of points returned, for a user-specified desired approximation, can be solved in polynomial time in two dimensions; for three and more it is NP-hard but has a polynomial-time logarithmic approximation. Finally, we present a polynomial-time, constant factor approximation algorithm for three dimensions.

Keywords

Greedy Algorithm Skyline Query Approximate Optimum Multimedia Database Constant Factor Approximation Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Vladlen Koltun
    • 1
  • Christos H. Papadimitriou
    • 1
  1. 1.Computer Science DivisionUniversity of CaliforniaBerkeleyUSA

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