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• W2744430135 startingPage "324" @default.
• W2744430135 abstract "Process 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." @default.
• W2744430135 created "2017-08-17" @default.
• W2744430135 creator A5035420876 @default.
• W2744430135 creator A5057742985 @default.
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• W2744430135 date "2017-01-01" @default.
• W2744430135 modified "2023-09-27" @default.
• W2744430135 title "Discovering Infrequent Behavioral Patterns in Process Models" @default.
• W2744430135 cites W1509056567 @default.
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• W2744430135 doi "https://doi.org/10.1007/978-3-319-65000-5_19" @default.
• W2744430135 hasPublicationYear "2017" @default.
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