Process mining has focused, among others, on the discov- ery of frequent behavior with the aim to understand what is mainly happening in a process. Little work has been done involving uncommon behavior, and mostly centered on the detection of anomalies or devia- tions. But infrequent behavior can be also important for the management of a process, as it can reveal, for instance, an uncommon wrong real- ization of a part of the process. In this paper, we present WoMine-i, a novel algorithm to retrieve infrequent behavioral patterns from a process model. Our approach searches in a process model extracting structures with sequences, selections, parallels and loops, which are infrequently executed in the logs. This proposal has been validated with a set of synthetic and real process models, and compared with state of the art techniques. Experiments show that WoMine-i can find all types of pat- terns, extracting information that cannot be mined with the state of the art techniques.
CITATION STYLE
Chapela-Campa, D., Mucientes, M., & Lama, M. (2017). Discovering Infrequent Behavioral Patterns in Process Models (pp. 324–340). https://doi.org/10.1007/978-3-319-65000-5_19
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