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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2019: Advances and Trends in Artificial Intelligence. From Theory to Practice pp 12–26Cite as

A Taxonomy of Event Prediction Methods

Part of the Lecture Notes in Computer Science book series (LNAI,volume 11606)

Abstract

Most of existing event prediction approaches consider event prediction problems within a specific application domain while event prediction is naturally a cross-disciplinary problem. This paper introduces a generic taxonomy of event prediction approaches. The proposed taxonomy, which oversteps the application domain, enables a better understanding of event prediction problems and allows conceiving and developing advanced and context-independent event prediction techniques.

Keywords

  • Time series
  • Event prediction
  • Taxonomy
  • Data mining

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Authors and Affiliations

  1. COSMOS, National School of Computer Sciences, University of Manouba, Manouba, Tunisia

    Fatma Ezzahra Gmati & Wided Lejouad Chaari

  2. Portsmouth Business School, University of Portsmouth, Portsmouth, UK

    Salem Chakhar & Mark Xu

  3. CORL, University of Portsmouth, Portsmouth, UK

    Salem Chakhar

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  1. Fatma Ezzahra Gmati
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  2. Salem Chakhar
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  3. Wided Lejouad Chaari
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  4. Mark Xu
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Correspondence to Salem Chakhar .

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Editors and Affiliations

  1. Institute for Software Technology, Graz University of Technology, Graz, Austria

    Prof. Dr. Franz Wotawa

  2. Department of Applied Informatics, University of Klagenfurt, Klagenfurt, Austria

    Dr. Gerhard Friedrich

  3. Institute for Software Technology, Graz University of Technology, Graz, Austria

    Dr. Ingo Pill

  4. Institute for Software Technology, Graz University of Technology, Graz, Austria

    Dr. Roxane Koitz-Hristov

  5. Department of Computer Science, Texas State University, San Marcos, TX, USA

    Dr. Moonis Ali

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Gmati, F.E., Chakhar, S., Chaari, W.L., Xu, M. (2019). A Taxonomy of Event Prediction Methods. In: Wotawa, F., Friedrich, G., Pill, I., Koitz-Hristov, R., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2019. Lecture Notes in Computer Science(), vol 11606. Springer, Cham. https://doi.org/10.1007/978-3-030-22999-3_2

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