QBHSQ: a quad-tree based algorithm for high-dimension skyline query

Authors:
Ma Zhixin;Xu Yusheng;Sheng Lijun;Li Lian
Affiliations:
School of Information Science and Engineering, Lanzhou University, China;School of Information Science and Engineering, Lanzhou University, China;School of Information Science and Engineering, Lanzhou University, China;School of Information Science and Engineering, Lanzhou University, China
Venue:
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Year:
2009

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Abstract

Query all skyline points in large high-dimension dataset is quite challenging and its space and computation overhead are massive. This paper presents QBHSQ, a novel Quad-tree based algorithm for skyline query in large high-dimension dataset. QBHSQ utilizes a partial dimension subset to partition dataset on high dimensional space by means of the configuration characters of quad-tree. Since amount of domination checking operators among non-domination subdatasets can be reduced and large numbers of data points in high dimensional space are deleted while constructing tree, QBHSQ contributes to a better computation and space performance than traditional ones. Extensive experiments demonstrate the efficiency and the scalability of proposed algorithm.