Data Requirements for Process Learning

Johny Ghattas, Mor Peleg, Pnina Soffer and Yaron Denekamp
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Johny Ghattas: University of Haifa, Haifa, Israel, & Smart Path Ltd, Jaffa-Tel-Aviv, Israel
Mor Peleg: Department of Information Systems, University of Haifa, Haifa, Israel
Pnina Soffer: Department of Information Systems, University of Haifa, Haifa, Israel
Yaron Denekamp: Faculty of Medicine, Galil Center for Medicial Informatics, Technion Institute of Technology, Haifa, Israel

International Journal of Knowledge-Based Organizations (IJKBO), 2013, vol. 3, issue 1, 1-18

Abstract: Process flexibility and adaptability is essential in environments where the processes are prompt to changes and variations. Process learning is a possible approach for automatically discovering from process log data those process paths that yielded good outcomes and suggesting appropriate process model modifications to enhance future process performance in such environments. The authors discuss and establish the data requirements for process learning, applicable to clinical process management. Their discussion extends a previously established learning process model (LPM) by providing a formal set of data requirements which enables the authors to accomplish effective learning. Learning data requirements are illustrated by walking through the application of the LPM framework to a clinical process.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jkbo00:v:3:y:2013:i:1:p:1-18

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