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Equilibrium Resolution for Epoch Partitioning

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Artificial Intelligence Applications and Innovations (AIAI 2022)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 647))

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Abstract

This paper proposes a method for determining the resolution for the processing of irregularly-sampled time series data to provide a balanced perspective of agents’ behaviour. The behaviour is described as a collection of prolonged events, which are characterised by start/open and end/close times in addition to other useful attributes. We propose the definition of an equilibrium resolution and carry out its analysis based on probabilistic assumptions. The resulting methods of determining the equilibrium resolution are tested on real-life time series data sets from the Financial and Travel problem domains.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Royal Holloway, University of London, Egham, UK

    Wojciech Wisniewski & Yuri Kalnishkan

  2. Algorithmic Laboratories Ltd., Ocean House, Bracknell, Berkshire, RG12 1AX, UK

    David Lindsay & Siân Lindsay

Authors
  1. Wojciech Wisniewski
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  2. Yuri Kalnishkan
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  3. David Lindsay
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  4. Siân Lindsay
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Corresponding authors

Correspondence to Wojciech Wisniewski or Yuri Kalnishkan .

Editor information

Editors and Affiliations

  1. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  2. Democritus University of Thrace, Xanthi, Greece

    Lazaros Iliadis

  3. University of Sunderland, Sunderland, UK

    John Macintyre

  4. Universidade do Minho, Guimaraes, Portugal

    Paulo Cortez

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Wisniewski, W., Kalnishkan, Y., Lindsay, D., Lindsay, S. (2022). Equilibrium Resolution for Epoch Partitioning. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 647. Springer, Cham. https://doi.org/10.1007/978-3-031-08337-2_32

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  • DOI: https://doi.org/10.1007/978-3-031-08337-2_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08336-5

  • Online ISBN: 978-3-031-08337-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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