Discovering Infrequent Behavioral Patterns in Process Models

TítuloDiscovering Infrequent Behavioral Patterns in Process Models
AutoresDavid Chapela-Campa, Manuel Mucientes, Manuel Lama
TipoComunicación para congreso
Fonte International Conference on Business Process Management, Barcelona (España), Springer, pp. 324-340 , 2017.
RankRanked A in CORE
ISBN978-3-319-64999-3
ISSN0302-9743
DOI10.1007/978-3-319-65000-5_19
AbstractProcess mining has focused, among others, on the discovery 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 deviations. But infrequent behavior can be also important for the management of a process, as it can reveal, for instance, an uncommon wrong realization 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 patterns, extracting information that cannot be mined with the state of the art techniques.
Palabras chaveInfrequent patterns, Process mining, Process discovery