Abstract-Within process mining research, one of the most important fields of study is process discovery, which can be defined as the extraction of control-flow models from audit trails or information system event logs. The evaluation of discovered process models is an essential but difficult task for any process discovery analysis. With this paper, we propose a novel approach for evaluating discovered process models based on artificially generated negative events. This approach allows for the definition of a behavioral F-measure for discovered process models, which is the main contribution of this paper.
Furthermore, our work reconsiders the definition of F-measure for Process Mining which has already been considered by REF that proposes a variant based on artificial generative negative events.
A robust F-measure for evaluating discovered process models
2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
Computer Science