Journal article

Split Miner: Automated Discovery of Accurate and Simple Business Process Models from Event Logs

A Augusto, R Conforti, M Dumas, M La Rosa, A Polyvyanyy

Knowledge and Information Systems | Springer Verlag | Published : 2019

Abstract

The problem of automated discovery of process models from event logs has been intensively researched in the past two decades. Despite a rich field of proposals, state-of-the-art automated process discovery methods suffer from two recurrent deficiencies when applied to real-life logs: (i) they produce large and spaghetti-like models; and (ii) they produce models that either poorly fit the event log (low fitness) or over-generalize it (low precision). Striking a trade-off between these quality dimensions in a robust and scalable manner has proved elusive. This paper presents an automated process discovery method, namely Split Miner, which produces simple process models with low branching compl..

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Grants

Awarded by Australian Research Council


Awarded by Estonian Research Council


Funding Acknowledgements

This research is partly funded by the Australian Research Council (Grant DP180102839) and the Estonian Research Council (Grant IUT20-55).