Abstract
Process Discovery techniques help a business analyst to understand the actual processes deployed in an organization, i.e. based on a log of events, the actual activity workflow is discovered. In most cases their results conform to general purpose representations like Petri nets or Causal nets which are preferred by academic scholars but difficult to comprehend for business analysts. In this paper we propose an algorithm that follows a top-down approach to directly mine a process model which consists of common BP-domain constructs and represents the main behaviour of the process. The algorithm is designed so it can deal with noise and not-supported behaviour. This is achieved by letting the different supported constructs compete with each other for the most suitable solution from top to bottom using ”soft” constraints and behaviour approximations. The key parts of the algorithm are formally described and evaluation results are presented and discussed.
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Redlich, D., Molka, T., Gilani, W., Blair, G., Rashid, A. (2014). Constructs Competition Miner: Process Control-Flow Discovery of BP-Domain Constructs. In: Sadiq, S., Soffer, P., Völzer, H. (eds) Business Process Management. BPM 2014. Lecture Notes in Computer Science, vol 8659. Springer, Cham. https://doi.org/10.1007/978-3-319-10172-9_9
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DOI: https://doi.org/10.1007/978-3-319-10172-9_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10171-2
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