Many human activities are nowadays very complex. Most of them are supported by information systems that record relevant events in logs, but are often not driven by, or even aware of, the underlying intended process models. However, process management systems can be useful in every aspect of life, not just in the traditional industrial and administrative domain. Process Discovery (PD) automatically learns pro- cess models from logs. Since the activities reported in logs are usually very fine-grained, most existing PD techniques (e.g., [1, 3]) produce ‘flat’, very complex and incomprehensible (‘spaghetti’), models, which are of little value.
Process Model Modularization by Subprocess Discovery
S. Angelastro;S. Ferilli
2019-01-01
Abstract
Many human activities are nowadays very complex. Most of them are supported by information systems that record relevant events in logs, but are often not driven by, or even aware of, the underlying intended process models. However, process management systems can be useful in every aspect of life, not just in the traditional industrial and administrative domain. Process Discovery (PD) automatically learns pro- cess models from logs. Since the activities reported in logs are usually very fine-grained, most existing PD techniques (e.g., [1, 3]) produce ‘flat’, very complex and incomprehensible (‘spaghetti’), models, which are of little value.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
