Equilibrium Resolution for Epoch Partitioning. / Wisniewski, Wojciech; Kalnishkan, Yuri; Lindsay, David; Lindsay, Sian.

Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations. Springer, 2022. (SPRINGER IFIP AICT).

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

Forthcoming

Documents

  • aiai2022_Equilibrium Resolution for Epoch Partitioning

    1.02 MB, PDF document

    Licence: CC BY Show licence

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.
Original languageEnglish
Title of host publicationProceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations
PublisherSpringer
Publication statusAccepted/In press - 31 Mar 2022
Event18th International Conference on Artificial Intelligence Applications and Innovations - Crete, Greece
Duration: 17 Jun 202220 Jun 2022
https://ifipaiai.org/2022/

Publication series

NameSPRINGER IFIP AICT

Conference

Conference18th International Conference on Artificial Intelligence Applications and Innovations
Abbreviated titleAIAI 2022
Country/TerritoryGreece
Period17/06/2220/06/22
Internet address

ID: 45327257