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A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining

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Applied Optimization and Swarm Intelligence

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

Numerical Association Rule Mining is a popular variant of Association Rule Mining, where numerical attributes are handled without discretization. This means that the algorithms for dealing with this problem can operate directly, not only with categorical, but also with numerical attributes. Until recently, a big portion of these algorithms were based on a stochastic nature-inspired population-based paradigm. As a result, evolutionary and swarm intelligence-based algorithms showed big efficiency for dealing with the problem. In line with this, the main mission of this chapter is to make a historical overview of swarm intelligence-based algorithms for Numerical Association Rule Mining, as well as to present the main features of these algorithms for the observed problem. A taxonomy of the algorithms was proposed on the basis of the applied features found in this overview. Challenges, waiting in the future, finish this paper.

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    https://scholar.google.com/.

  2. 2.

    www.scopus.com.

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    https://ieeexplore.ieee.org/Xplore/home.jsp.

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, Maribor, Slovenia

    Iztok Fister Jr. & Iztok Fister

Authors
  1. Iztok Fister Jr.
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  2. Iztok Fister
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Correspondence to Iztok Fister Jr. .

Editor information

Editors and Affiliations

  1. Tecnalia Research and Innovation, BRTA (Basque Research and Technology Alliance), Derio, Spain

    Eneko Osaba

  2. Department of Design Engineering and Mathematics, School of Science and Technology, Middlesex University, London, UK

    Xin-She Yang

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Fister Jr., I., Fister, I. (2021). A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining. In: Osaba, E., Yang, XS. (eds) Applied Optimization and Swarm Intelligence. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-16-0662-5_3

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