Incremental evaluation of top-? combinatorial metric skyline query

T. Jiang, B. Zhang, D. Lin, Y. Gao, Qing Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)


© 2014 Elsevier B.V. All rights reserved.In this paper, we define a novel type of skyline query, namely top-? combinatorial metric skyline (?CMS) query. The ?CMS query aims to find k combinations of data points according to a monotonic preference function such that each combination has the query object in its metric skyline. The ?CMS query will enable a new set of location-based applications that the traditional skyline queries cannot offer. To answer the ?CMS query, we propose two efficient query algorithms, which leverage a suite of techniques including the sorting and threshold mechanisms, reusing technique, and heuristics pruning to incrementally and quickly generate combinations of possible query results. We have conducted extensive experimental studies, and the results demonstrate both effectiveness and efficiency of our proposed algorithms.
Original languageEnglish
Pages (from-to)89-105
Number of pages17
JournalKnowledge-Based Systems
Publication statusPublished - 1 Jan 2015
Externally publishedYes


  • Algorithm
  • Combinational skyline
  • Metric skyline
  • Query processing
  • Spatial database

ASJC Scopus subject areas

  • Software
  • Management Information Systems
  • Information Systems and Management
  • Artificial Intelligence


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