Partial order resolution of event logs for process conformance checking

Aa, Han van der ; Leopold, Henrik ; Weidlich, Matthias

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Document Type: Article
Year of publication: 2020
The title of a journal, publication series: Decision Support Systems : DSS
Volume: 136
Issue number: Article 113347
Page range: 1-34
Place of publication: Amsterdam [u.a.]
Publishing house: Elsevier
ISSN: 0167-9236 , 1873-5797
Publication language: English
Institution: School of Business Informatics and Mathematics > Methoden der künstlichen Intelligenz (Juniorprofessur) (van der Aa 2020-)
Subject: 004 Computer science, internet
Abstract: While supporting the execution of business processes, information systems record event logs. Conformance checking relies on these logs to analyze whether the recorded behavior of a process conforms to the behavior of a normative specification. A key assumption of existing conformance checking techniques, however, is that all events are associated with timestamps that allow to infer a total order of events per process instance. Unfortunately, this assumption is often violated in practice. Due to synchronization issues, manual event recordings, or data corruption, events are only partially ordered. In this paper, we put forward the problem of partial order resolution of event logs to close this gap. It refers to the construction of a probability distribution over all possible total orders of events of an instance. To cope with the order uncertainty in real-world data, we present several estimators for this task, incorporating different notions of behavioral abstraction. Moreover, to reduce the runtime of conformance checking based on partial order resolution, we introduce an approximation method that comes with a bounded error in terms of accuracy. Our experiments with real-world and synthetic data reveal that our approach improves accuracy over the state-of-the-art considerably.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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