Software process validation: quantitatively measuring the correspondence of a process to a model
ACM Transactions on Software Engineering and Methodology (TOSEM)
Genetic process mining: an experimental evaluation
Data Mining and Knowledge Discovery
Conformance checking of processes based on monitoring real behavior
Information Systems
The refined process structure tree
Data & Knowledge Engineering
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Simplified computation and generalization of the refined process structure tree
WS-FM'10 Proceedings of the 7th international conference on Web services and formal methods
Conformance Checking Using Cost-Based Fitness Analysis
EDOC '11 Proceedings of the 2011 IEEE 15th International Enterprise Distributed Object Computing Conference
Distributed process discovery and conformance checking
FASE'12 Proceedings of the 15th international conference on Fundamental Approaches to Software Engineering
Replaying history on process models for conformance checking and performance analysis
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Decomposing process mining problems using passages
PETRI NETS'12 Proceedings of the 33rd international conference on Application and Theory of Petri Nets
Process Discovery and Conformance Checking Using Passages
Fundamenta Informaticae - Application and Theory of Petri Nets and Concurrency, 2012
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The torrents of event data generated by today's systems are an important enabler for process mining. However, at the same time, the size and variability of the resulting event logs are challenging for today's process mining techniques. This paper focuses on "conformance checking in the large" and presents a novel decomposition technique that partitions larger processes into sets of subprocesses that can be analyzed more easily. The resulting topological representation of the partitioning can be used to localize conformance problems. Moreover, we provide techniques to refine the decomposition such that similar process fragments are not considered twice during conformance analysis. All the techniques have been implemented in ProM, and experimental results are provided.