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A taxonomy of event prediction methods

Research output: Chapter in Book/Report/Conference proceedingConference contribution

An event is a timestamped element in a temporal sequence. Event prediction problem concerns the prediction of one or several elements constituting the future characteristics of the event. A large number of event prediction approaches have been proposed in the literature but most of existing works consider event prediction problem within a specific application domain while event prediction is naturally a cross-disciplinary problem. This paper introduces a generic taxonomy of event prediction approaches that go beyond the problem considered and application domain. This generic view enables a better understanding of event prediction problems and allows conceiving and developing advanced and context-independent event prediction techniques.
Original languageEnglish
Title of host publicationAdvances and Trends in Artificial Intelligence. From Theory to Practice
Subtitle of host publication32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Graz, Austria, July 9–11, 2019, Proceedings
EditorsFranz Wotawa, Gerhard Friedrich, Ingo Pill, Roxane Koitz-Hristov, Ali Moonis
Place of PublicationSwitzerland
PublisherSpringer International Publishing
Pages12-26
Number of pages14
ISBN (Electronic)978-3-030-22999-3
ISBN (Print)978-3-030-22998-6
DOIs
Publication statusPublished - Jul 2019
Event32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems - Graz, Austria
Duration: 9 Jul 201911 Jul 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11606
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems
Abbreviated titleIEA/AIE 2019
CountryAustria
CityGraz
Period9/07/1911/07/19

Documents

  • Gmati-etal_iea-aie2019_cr

    Rights statement: The final authenticated version is available online at: http://dx.doi.org/10.1007%2F978-3-030-22999-3_2.

    Accepted author manuscript (Post-print), 964 KB, PDF document

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Relations Get citation (various referencing formats)

ID: 13460744