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

E-pub ahead of print

Standard

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

Harvard

Wisniewski, W, Kalnishkan, Y, Lindsay, D & Lindsay, S 2022, Equilibrium Resolution for Epoch Partitioning. in Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations. SPRINGER IFIP AICT, Springer, 18th International Conference on Artificial Intelligence Applications and Innovations, Greece, 17/06/22.

APA

Wisniewski, W., Kalnishkan, Y., Lindsay, D., & Lindsay, S. (2022). Equilibrium Resolution for Epoch Partitioning. In Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations (SPRINGER IFIP AICT). Springer.

Vancouver

Wisniewski W, Kalnishkan Y, Lindsay D, Lindsay S. Equilibrium Resolution for Epoch Partitioning. In Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations. Springer. 2022. (SPRINGER IFIP AICT).

Author

Wisniewski, Wojciech ; Kalnishkan, Yuri ; Lindsay, David ; Lindsay, Sian. / Equilibrium Resolution for Epoch Partitioning. Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations. Springer, 2022. (SPRINGER IFIP AICT).

BibTeX

@inproceedings{9d6187b49b9947bb94e309ea0980fca5,
title = "Equilibrium Resolution for Epoch Partitioning",
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.",
keywords = "Time Series Resolution, Time Series Partitioning, database management, Big Data",
author = "Wojciech Wisniewski and Yuri Kalnishkan and David Lindsay and Sian Lindsay",
year = "2022",
month = jun,
day = "10",
language = "English",
series = "SPRINGER IFIP AICT",
publisher = "Springer",
booktitle = "Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations",
note = "18th International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022 ; Conference date: 17-06-2022 Through 20-06-2022",
url = "https://ifipaiai.org/2022/",

}

RIS

TY - GEN

T1 - Equilibrium Resolution for Epoch Partitioning

AU - Wisniewski, Wojciech

AU - Kalnishkan, Yuri

AU - Lindsay, David

AU - Lindsay, Sian

PY - 2022/6/10

Y1 - 2022/6/10

N2 - 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.

AB - 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.

KW - Time Series Resolution

KW - Time Series Partitioning

KW - database management

KW - Big Data

M3 - Conference contribution

T3 - SPRINGER IFIP AICT

BT - Proceedings of the 18th International Conference on Artificial Intelligence Applications and Innovations

PB - Springer

T2 - 18th International Conference on Artificial Intelligence Applications and Innovations

Y2 - 17 June 2022 through 20 June 2022

ER -