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Progressive approaches to flexible group skyline queries

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Abstract

The G-Skyline (GSky) query is formulated to report optimal groups that are not dominated by any other group of the same size. Particularly, a given group \(G_1\) dominates another group \(G_2\) if for any point \(p\in G_1\), p dominates or equals to points \(p{'}\in G_2\); at the same time, there is at least one point p dominating \(p{'}\). Most existing group skyline queries need to calculate an aggregate point for each group. Compared to these queries, the GSky query is more practical because it avoids specifying an aggregate function which leads to miss important results containing non-skyline points. This means the GSky query can get much more comprehensive query results which not only contain the G-Skylines consisting of skyline points but also the G-Skylines including non-skyline points. Here, a non-skyline point is dominated by another point in a given data set. However, the GSky query usually returns too many results, making it a big burden for users to pick out their expected results. To address these issues, we investigate a flexible group skyline query, namely Flexible G-Skyline (FGSky) query, which is flexible and practical for directly computing the optimal groups on the basis of user preferences. In this paper, we formulate the FGSky query, identify its properties, and present effective pruning strategies. Besides, we propose progressive algorithms for the FGSky query where a grouping strategy and a layered strategy are utilized to get better query performance. Through extensive experiments on both synthetic and real data sets, we demonstrate the efficiency, effectiveness, and progressiveness of the proposed algorithms.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable and helpful comments on improving the manuscript. The research was supported by the NSFC (Grant Nos. 61802032, 61772182, 61602170), the Key Program of NSFC (Grant No. 61432005), the International (Regional) Cooperation and Exchange Program of NSFC (Grant No. 61661146006), the Emergency Special Project of NSFC (Grant No. 61751204), the Key Area Research Program of Hunan (2019GK2091), and the Hunan Province Key Laboratory of Industrial Internet Technology and Security (2019TP1011). Xu Zhou is the corresponding author of this paper.

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Authors and Affiliations

  1. Hunan Province Key Laboratory of Industrial Internet Technology and Security, Changsha University, Changsha, 410003, Hunan, China

    Zhibang Yang

  2. School of Information Science and Engineering, Hunan University, Changsha, 410082, Hunan, China

    Xu Zhou, Kenli Li & Keqin Li

  3. Department of Computer Science, State University of New York, New Paltz, NY, 12561, USA

    Keqin Li

  4. College of Computer Science, Zhejiang University, Hangzhou, 310027, Zhejiang, China

    Yunjun Gao

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  1. Zhibang Yang
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  2. Xu Zhou
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  3. Kenli Li
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  4. Yunjun Gao
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  5. Keqin Li
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Correspondence to Xu Zhou.

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Yang, Z., Zhou, X., Li, K. et al. Progressive approaches to flexible group skyline queries. Knowl Inf Syst 63, 1471–1496 (2021). https://doi.org/10.1007/s10115-021-01562-8

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