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Semantic Business Process Mining of SAP Transactions

Semantic Business Process Mining of SAP Transactions

Jon Espen Ingvaldsen, Jon Atle Gulla
Copyright: © 2010 |Pages: 14
ISBN13: 9781605666693|ISBN10: 1605666696|EISBN13: 9781605666709
DOI: 10.4018/978-1-60566-669-3.ch017
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MLA

Ingvaldsen, Jon Espen, and Jon Atle Gulla. "Semantic Business Process Mining of SAP Transactions." Handbook of Research on Complex Dynamic Process Management: Techniques for Adaptability in Turbulent Environments, edited by Minhong Wang and Zhaohao Sun, IGI Global, 2010, pp. 416-429. https://doi.org/10.4018/978-1-60566-669-3.ch017

APA

Ingvaldsen, J. & Gulla, J. (2010). Semantic Business Process Mining of SAP Transactions. In M. Wang & Z. Sun (Eds.), Handbook of Research on Complex Dynamic Process Management: Techniques for Adaptability in Turbulent Environments (pp. 416-429). IGI Global. https://doi.org/10.4018/978-1-60566-669-3.ch017

Chicago

Ingvaldsen, Jon Espen, and Jon Atle Gulla. "Semantic Business Process Mining of SAP Transactions." In Handbook of Research on Complex Dynamic Process Management: Techniques for Adaptability in Turbulent Environments, edited by Minhong Wang and Zhaohao Sun, 416-429. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-669-3.ch017

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Abstract

This chapter introduces semantic business process mining of SAP transaction logs. SAP systems are promising domains for semantic process mining as they contain transaction logs that are linked to large amounts of structured data. A challenge with process mining these transaction logs is that the core of SAP systems was not originally designed from the business process management perspective. The business process layer was added later without full rearrangement of the system. As a result, system logs produced by SAP are not process-based, but transaction-based. This means that the system does not produce traces of process instances that are needed for process mining. In this chapter, we show how data available in SAP systems can enrich process instance logs with ontologically structured concepts, and evaluate techniques for mapping executed transaction sequences with predefined process hierarchies.

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