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 language | English |
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Title of host publication | Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations |
Publisher | Springer |
Publication status | E-pub ahead of print - 10 Jun 2022 |
Event | 18th International Conference on Artificial Intelligence Applications and Innovations - Crete, Greece Duration: 17 Jun 2022 → 20 Jun 2022 https://ifipaiai.org/2022/ |
Publication series
Name | SPRINGER IFIP AICT |
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Conference
Conference | 18th International Conference on Artificial Intelligence Applications and Innovations |
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Abbreviated title | AIAI 2022 |
Country/Territory | Greece |
Period | 17/06/22 → 20/06/22 |
Internet address |
Keywords
- Time Series Resolution
- Time Series Partitioning
- database management
- Big Data