Skyline: Stacking Optimal Solutions in Exact and Uncertain Worlds
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Wenjie Zhang,Muhammad Aamir Cheema,Ying Zhang,Xuemin Lin. Skyline: Stacking Optimal Solutions in Exact and Uncertain Worlds. International Journal of Software and Informatics, 2012,6(4):475~493
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Fund:This work is sponsored by ARC DP120104168 and ARC DE120102144 (Wenjie Zhang); ARC DP110104880 and UNSW ECR grant PS27476 (Ying Zhang); ARC DP0987557, ARC DP110102937, ARC DP120104168, and NSFC61021004 (Xuemin Lin).
Abstract:In many applications involving multiple criteria optimal decision making, users may often want to make a personal trade-off among all optimal solutions for selecting one object that best fits their personal needs. As a key feature, skyline in a multi-dimensional space provides a minimal set of candidates for such purposes by removing every object that is not preferred by any (monotonic) utility/scoring function; that is, the skyline removes all objects not preferred by any user no matter how their preferences vary. Due to its importance, the problem of skyline computation and its variants have been extensively studied in the database literature. In this paper, we provide a comprehensive survey of skyline computation techniques. Specifically, we first introduce the skyline computation algorithms on traditional (exact) data where each object corresponds to a point in a multi-dimensional space. Then, we discuss the skyline models and effcient algorithms to handle uncertain data which is inherent in many important applications. Finally, we briefly describe a few variants of the skyline (e.g., skycube, k-skyband and reverse skyline) in this paper.
keywords:query processing  skyline  uncertain data
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