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

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 propos- als, 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 tradeoff between these quality di- mensions 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 co..