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Top-k Combinatorial Skyline Queries

  • I-Fang Su
  • Yu-Chi Chung
  • Chiang Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5982)

Abstract

The problem of top-k skyline computation has attracted considerable research attention in the past few years. Given a dataset, a top-k skyline returns k “most interesting” skyline tuples based on some kind of preference specified by the user. We extend the concept of top-k skyline to a so-called top-k combinatorial skyline query (k-CSQ). In contrast to the existing top-k skyline query (which is mainly to find the interesting skyline tuples), a k-CSQ is to find the interesting skyline tuples from various kinds of combinations of the given tuples. The k-CSQ is an important tool for areas such as decision making, market analysis, business planning, and quantitative economics research. In this paper, we will formally define this new problem, propose an intelligent method to resolve this problem, and also conduct a set of experiments to show the effectiveness and efficiency of the proposed algorithm.

Keywords

User Preference Query Time Investment Portfolio Large Data Base Skyline Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • I-Fang Su
    • 1
  • Yu-Chi Chung
    • 2
  • Chiang Lee
    • 1
  1. 1.Department of Computer Science and Information EngineeringNational Cheng-Kung UniversityTainanTaiwan, R.O.C.
  2. 2.Department of Computer Science and Information EngineeringChang Jung Christian UniversityTainanTaiwan, R.O.C.

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