Finding the most desirable skyline objects

Authors:
Yunjun Gao;Junfeng Hu;Gencai Chen;Chun Chen
Affiliations:
College of Computer Science and Technology, Zhejiang University;School of Computing, National University of Singapore;College of Computer Science and Technology, Zhejiang University;College of Computer Science and Technology, Zhejiang University
Venue:
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Year:
2010

Citing 11
Cited 1

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Abstract

This paper introduces a new operator, namely the most desirable skyline object (MDSO) query, to identify manageable size of truly interesting skyline objects. Given a set of multi-dimensional objects and an integer k, a MDSO query retrieves the most preferablek skyline objects, based on the newly defined ranking criterion that considers, for each skyline object s, the number of objects dominated by s and their accumulated (potential) weight. We present the ranking criterion, formalize the MDSO query, and develop two algorithms for processing MDSO queries assuming that the dataset is indexed by a traditional data-partitioning index. Extensive experiments demonstrate the performance of the proposed algorithms.