Automated discovery of structured process models: Discover structured vs discover and structure

Augusto, Adriano, Conforti, Raffaele, Dumas, Marlon, La Rosa, Marcello, & Bruno, Giorgio (2016) Automated discovery of structured process models: Discover structured vs discover and structure. In 35th International Conference on Conceptual Modeling (ER2016), 14-17 November 2016, Gifu, Japan.

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Abstract

This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.

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ID Code: 95189
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Process Mining, Business Process Management, Structured Processes, Process Structuring
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Systems Management (080609)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Systems not elsewhere classified (080699)
Divisions: Current > Institutes > Institute for Future Environments
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 [please consult the authors]
Deposited On: 27 Apr 2016 01:22
Last Modified: 09 Dec 2016 02:52

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