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On Controlling Skyline Query Results: What Does Soft Computing Bring?

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Flexible Query Answering Systems (FQAS 2021)

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Abstract

Querying databases to search for the best objects matching user’s preferences is a fundamental problem in multi-criteria databases. The skyline queries are an important tool for solving such problems. Based on the concept of Pareto dominance, the skyline process extracts the most interesting (not dominated in Pareto sense) objects from a set of data. However, this process may often lead to the two scenarios: (i) a small number of skyline objects are retrieved which could be insufficient to serve the decision makers’needs ; (ii) a huge number of skyline objects are returned which are less informative for the decision makers. In this paper, we discuss and show how Soft Computing, and more particularly fuzzy set theory, can contribute to solve the two above problems. First, a relaxation mechanism to enlarge the skyline set is presented. It relies on a particular fuzzy preference relation, called “much preferred”. Second, an efficient approach to refine huge skyline and reduce its size, using some advanced techniques borrowed from fuzzy formal concepts analysis, is provided. The approaches proposed are user-dependent and allow controlling the skyline results in a flexible and rational way.

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Notes

  1. 1.

    \( \mathcal {M} \)uch \( \mathcal {P} \)referred \( \mathcal {R} \)elation for \( \mathcal {R} \)elaxation.

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Correspondence to Allel Hadjali .

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Hadjali, A. (2021). On Controlling Skyline Query Results: What Does Soft Computing Bring?. In: Andreasen, T., De Tré, G., Kacprzyk, J., Legind Larsen, H., Bordogna, G., Zadrożny, S. (eds) Flexible Query Answering Systems. FQAS 2021. Lecture Notes in Computer Science(), vol 12871. Springer, Cham. https://doi.org/10.1007/978-3-030-86967-0_8

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  • DOI: https://doi.org/10.1007/978-3-030-86967-0_8

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