Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces

The skyline operator is important for multicriteria decision making applications. Although many recent studies developed efficient methods to compute skyline objects in a specific space, the fundamental problem on the semantics of skylines remains open: Why and in which subspaces is (or is not) an object in the skyline? Practically, users may also be interested in the skylines in any subspaces. Then, what is the relationship between the skylines in the subspaces and those in the super-spaces? How can we effectively analyze the subspace skylines? Can we efficiently compute skylines in various subspaces? In this paper, we investigate the semantics of skylines, propose the subspace skyline analysis, and extend the full-space skyline computation to subspace skyline computation. We introduce a novel notion of skyline group which essentially is a group of objects that are coincidentally in the skylines of some subspaces. We identify the decisive subspaces that qualify skyline groups in the subspace skylines. The new notions concisely capture the semantics and the structures of skylines in various subspaces. Multidimensional roll-up and drilldown analysis is introduced. We also develop an efficient algorithm, Skyey, to compute the ∗ The research of Jian Pei is supported in part by NSERC Grant 312194-05 and NSF Grant IIS-0308001. The research of Yufei Tao is supported in part by Grant CityU 1163/04E from the RGC of HKSAR. All opinions, findings, conclusions and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Proceedings of the 31st VLDB Conference, Trondheim, Norway, 2005 set of skyline groups and, for each subspace, the set of objects that are in the subspace skyline. A performance study is reported to evaluate our approach.