Abstract
Business processes are dynamic and change due to diverse factors. While existing approaches aim to detect drifts in the process structure, Tesseract looks for temporal drifts in activity interim times. This orthogonal view on the process extends the traditional data cube of events - case id, activities and timestamps - by a fourth dimension and improves the operational support by a visualization of temporal drifts in real-time. Insights about temporal deviations lead to an augmented awareness of imminent failures or improved service times. The detection of related structural concept drifts can be improved by early warning, as operation times of critical parts often increase before they catastrophically fail. (C) 2018 Elsevier Ltd. All rights reserved.
Item Type: | Journal article |
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Faculties: | Mathematics, Computer Science and Statistics > Computer Science |
Subjects: | 000 Computer science, information and general works > 004 Data processing computer science |
ISSN: | 0306-4379 |
Language: | English |
Item ID: | 82231 |
Date Deposited: | 15. Dec 2021, 15:00 |
Last Modified: | 13. Aug 2024, 13:00 |