On skyline groups

Nan Zhang, Chengkai Li, Naeemul Hassan, Sundaresan Rajasekaran, Gautam Das

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

We formulate and investigate the novel problem of finding the skyline k-tuple groups from an n-tuple data set - i.e., groups of k tuples which are not dominated by any other group of equal size, based on aggregate-based group dominance relationship. The major technical challenge is to identify effective anti-monotonic properties for pruning the search space of skyline groups. To this end, we first show that the anti-monotonic property in the well-known Apriori algorithm does not hold for skyline group pruning. Then, we identify two anti-monotonic properties with varying degrees of applicability: order-specific property which applies to SUM, MIN, and MAX as well as weak candidate-generation property which applies to MIN and MAX only. Experimental results on both real and synthetic data sets verify that the proposed algorithms achieve orders of magnitude performance gain over the baseline method.

Original languageEnglish (US)
Article number6559976
Pages (from-to)942-956
Number of pages15
JournalIEEE Transactions on Knowledge and Data Engineering
Volume26
Issue number4
DOIs
StatePublished - Jan 1 2014

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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    Zhang, N., Li, C., Hassan, N., Rajasekaran, S., & Das, G. (2014). On skyline groups. IEEE Transactions on Knowledge and Data Engineering, 26(4), 942-956. [6559976]. https://doi.org/10.1109/TKDE.2013.119