Efficient Computation of a Skyline under Location Restrictions


The KIPS Transactions:PartD, Vol. 18, No. 5, pp. 313-316, Oct. 2011
10.3745/KIPSTD.2011.18.5.313,   PDF Download:

Abstract

The skyline of a multi-dimensional data set is a subset that consists of the data that are not dominated by other members of the set. Skyline computation can be very useful for decision making for multi-dimensional data set. However, in case that the skyline is very large, it may not be much useful for decision making. In this paper, we propose an algorithm for computing a part of the skyline considering location restrictions that the user provides, such as origin movement, degree ranges and/or distances from the origin. The algorithm eliminates noncandidate data rapidly, and returns in order the skyline points that satisfy the user`s requests. We show that the algorithm is efficient by experiments.


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Cite this article
[IEEE Style]
J. H. Kim and M. Kim, "Efficient Computation of a Skyline under Location Restrictions," The KIPS Transactions:PartD, vol. 18, no. 5, pp. 313-316, 2011. DOI: 10.3745/KIPSTD.2011.18.5.313.

[ACM Style]
Ji Hyun Kim and Myung Kim. 2011. Efficient Computation of a Skyline under Location Restrictions. The KIPS Transactions:PartD, 18, 5, (2011), 313-316. DOI: 10.3745/KIPSTD.2011.18.5.313.