Exploring Business Process Deviance with Declare
Name
Juraj Jarabek
Abstract
This thesis introduces business process deviance mining, which belongs to the group
of process mining, and gives an overview on multiple deviance mining approaches. After that
we focus on deviance mining using discriminative patterns, which belongs to the group of
sequential patterns mining techniques. In this work we propose new discriminative pattern
mining algorithm based on the Declare language. We implemented the approach as a plug-in
of the Process Mining tool ProM. We describe the whole proposed approach from the labelling
of the event logs until building the classifier and classifying the test logs. In the end of the
thesis we evaluate the effectiveness of our proposed algorithm on variety of experiments on
event logs.
of process mining, and gives an overview on multiple deviance mining approaches. After that
we focus on deviance mining using discriminative patterns, which belongs to the group of
sequential patterns mining techniques. In this work we propose new discriminative pattern
mining algorithm based on the Declare language. We implemented the approach as a plug-in
of the Process Mining tool ProM. We describe the whole proposed approach from the labelling
of the event logs until building the classifier and classifying the test logs. In the end of the
thesis we evaluate the effectiveness of our proposed algorithm on variety of experiments on
event logs.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Fabrizio Maria Maggi, Fredrik Milani
Defence year
2016