Treffer: Approximately dominating representatives

Title:
Approximately dominating representatives
Source:
Database theoryTheoretical computer science. 371(3):148-154
Publisher Information:
Amsterdam: Elsevier, 2007.
Publication Year:
2007
Physical Description:
print, 16 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Computer Science Division, University of California, Berkeley, CA 94720-1776, United States
ISSN:
0304-3975
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.18568762
Database:
PASCAL Archive

Weitere Informationen

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 [Kian-Lee Tan, Pin-Kwang Eng, Beng Chin Ooi, Efficient progressive skyline computation, in: VLDB, 2001, pp. 301-310; Wolf-Tilo Balke, Ulrich Giintzer, Jason Xin Zheng, Efficient distributed skylining for web information systems, in: EDBT, 2004. [14]]. 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.