Organizations collect and store considerable amounts of process data in event logs that are subsequently mined to obtain process models. When the business process involves hundreds of activities, executed according to complex execution patterns, the process model can become too large and complex to identify relevant information by manual and visual inspection only. Summarization techniques can help, by providing concise and meaningful representations of the underling process. This paper describes a business process summarization algorithm based on the hierarchical grouping of activities. In the proposed approach, activity grouping is guided by the existence of some relations, between pairs of activities, mined from the associated event log.

Control-Flow Business Process Summarization via Activity Contraction

Fionda V.;Greco Gianluigi
2019

Abstract

Organizations collect and store considerable amounts of process data in event logs that are subsequently mined to obtain process models. When the business process involves hundreds of activities, executed according to complex execution patterns, the process model can become too large and complex to identify relevant information by manual and visual inspection only. Summarization techniques can help, by providing concise and meaningful representations of the underling process. This paper describes a business process summarization algorithm based on the hierarchical grouping of activities. In the proposed approach, activity grouping is guided by the existence of some relations, between pairs of activities, mined from the associated event log.
978-3-030-33616-5
978-3-030-33617-2
Business process; Process Mining; Summarization
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/303710
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