Process Mining attempts to reconstruct the workflow of a business process from logs of activities. This task is quite important in business scenarios where there is not a well understood and structured definition of the business process performed by workers. Activities logs are thus mined in the attempt to reconstruct the actual business process. In this paper, we propose the generalization of a popular process mining algorithm, named Heuristics Miner, to time intervals. We show that the possibility to use, when available, time interval information for the per- formed activities allows the algorithm to produce better workflow models.

Heuristics Miner for Time Intervals

SPERDUTI, ALESSANDRO
2010

Abstract

Process Mining attempts to reconstruct the workflow of a business process from logs of activities. This task is quite important in business scenarios where there is not a well understood and structured definition of the business process performed by workers. Activities logs are thus mined in the attempt to reconstruct the actual business process. In this paper, we propose the generalization of a popular process mining algorithm, named Heuristics Miner, to time intervals. We show that the possibility to use, when available, time interval information for the per- formed activities allows the algorithm to produce better workflow models.
2010
Proceedings of 18th European Symposium On Artificial Neural Networks, Computational Intelligence and Machine Learning
2930307102
9782930307107
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2420577
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