On space constrained set selection problems

  • Authors:
  • Themis Palpanas;Nick Koudas;Alberto Mendelzon

  • Affiliations:
  • University of Trento, Via Sommarive 14, Povo, Italy;University of Toronto, 40 St. George Street, Toronto, Canada;University of Toronto, 40 St. George Street, Toronto, Canada

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2008

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Abstract

Space constrained optimization problems arise in a variety of applications, ranging from databases to ubiquitous computing. Typically, these problems involve selecting a set of items of interest, subject to a space constraint. We show that in many important applications, one faces variants of this basic problem, in which the individual items are sets themselves, and each set is associated with a benefit value. Since there are no known approximation algorithms for these problems, we explore the use of greedy and randomized techniques. We present a detailed performance and theoretical evaluation of the algorithms, highlighting the efficiency of the proposed solutions.