Towards a Transition Matrix-Based Concept Drift Approach: Experiments on the Detection Task

Antonio Carlos Meira Neto, Rafael Gaspar de Sousa, Marcelo Fantinato, Sarajane Peres

2023

Abstract

Contemporary process mining techniques commonly assume business processes are in a steady state. However, business processes are prone to change and evolution in response to various factors, which can happen at any time, in a planned or unplanned way. This phenomenon of business process evolution and change is known as concept drift, and identifying and understanding is of paramount relevance for business process management, so that organizations can respond and adapt to the new challenges they face. The goal of this paper is to introduce the use of transformed transition matrices as a data structure to support the treatment of concept drifts in process mining, given its efficiency, simplicity, and expandability. The proposed data structure allows to handle different concept drift aspects in an integrated way. Three concept drift detection methods are first adapted to work on transformed transition matrices. The results obtained in the experiments are compared with a state-of-the-art method (baseline), and the three methods used achieved good results, showing an encouraging potential for future planned work.

Paper Citation

in Harvard Style

Carlos Meira Neto A., Gaspar de Sousa R., Fantinato M. and Peres S. (2023). Towards a Transition Matrix-Based Concept Drift Approach: Experiments on the Detection Task. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-648-4, SciTePress, pages 361-372. DOI: 10.5220/0011843600003467

in Bibtex Style

@conference{iceis23,
author={Antonio Carlos Meira Neto and Rafael Gaspar de Sousa and Marcelo Fantinato and Sarajane Peres},
title={Towards a Transition Matrix-Based Concept Drift Approach: Experiments on the Detection Task},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2023},
pages={361-372},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011843600003467},
isbn={978-989-758-648-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Towards a Transition Matrix-Based Concept Drift Approach: Experiments on the Detection Task
SN - 978-989-758-648-4
AU - Carlos Meira Neto A.
AU - Gaspar de Sousa R.
AU - Fantinato M.
AU - Peres S.
PY - 2023
SP - 361
EP - 372
DO - 10.5220/0011843600003467
PB - SciTePress