Improving the quality of the Heuristics Miner in ProM 6.2

Sofie De Cnudde, Jan Claes, Geert Poels
Expert Systems with Applications, Vol 41 (17), p. 7678-7690, 2014 (WoS IF '14: 2,240 (Q1, top 10%)) (Scopus CS '14: 3,63 (Q1, top 3%)) pdf
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Abstract. Considering the presence of large amounts of data in organizations today, the need to transform this data into useful information and subsequently into knowledge, increasingly gains attention. Process discovery is a technique to automatically discover process models from data in event logs. Since process discovery is gaining attention among researchers and practitioners, the quality of the resulting process model must be assured. In this paper, the quality of the frequently used Heuristics Miner is improved as anomalies were found concerning the validity and completeness of the resulting process model. For this purpose, a new artifact called the Updated Heuristics Miner was constructed containing alterations to the tool and to the algorithm itself. Evaluations of this artifact resulted in the conclusion that the Updated Heuristics Miner indeed demonstrates higher validity and completeness and that there is a need for a systematic evaluation method for process discovery techniques.