Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Software process validation: quantitatively measuring the correspondence of a process to a model
ACM Transactions on Software Engineering and Methodology (TOSEM)
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Modular Analysis of Systems Composed of Semiautonomous Subsystems
ACSD '04 Proceedings of the Fourth International Conference on Application of Concurrency to System Design
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Genetic process mining: an experimental evaluation
Data Mining and Knowledge Discovery
Rediscovering workflow models from event-based data using little thumb
Integrated Computer-Aided Engineering
Conformance checking of processes based on monitoring real behavior
Information Systems
A Region-Based Algorithm for Discovering Petri Nets from Event Logs
BPM '08 Proceedings of the 6th International Conference on Business Process Management
Using minimum description length for process mining
Proceedings of the 2009 ACM symposium on Applied Computing
Robust Process Discovery with Artificial Negative Events
The Journal of Machine Learning Research
Divide-and-Conquer Strategies for Process Mining
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Process Discovery using Integer Linear Programming
Fundamenta Informaticae - Petri Nets 2008
Process mining based on regions of languages
BPM'07 Proceedings of the 5th international conference on Business process management
A fresh look at precision in process conformance
BPM'10 Proceedings of the 8th international conference on Business process management
Process mining meets abstract interpretation
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Soundness of workflow nets: classification, decidability, and analysis
Formal Aspects of Computing
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Cost-Based Fitness in Conformance Checking
ACSD '11 Proceedings of the 2011 Eleventh International Conference on Application of Concurrency to System Design
Conformance Checking Using Cost-Based Fitness Analysis
EDOC '11 Proceedings of the 2011 IEEE 15th International Enterprise Distributed Object Computing Conference
Process mining from a basis of state regions
PETRI NETS'10 Proceedings of the 31st international conference on Applications and Theory of Petri Nets
Distributed data mining on grids: services, tools, and applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Towards distributed verification of petri nets properties
VECoS'07 Proceedings of the First international conference on Verification and Evaluation of Computer and Communication Systems
Replaying history on process models for conformance checking and performance analysis
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Understanding process behaviours in a large insurance company in Australia: a case study
CAiSE'13 Proceedings of the 25th international conference on Advanced Information Systems Engineering
Hierarchical conformance checking of process models based on event logs
PETRI NETS'13 Proceedings of the 34th international conference on Application and Theory of Petri Nets and Concurrency
Conformance checking in the large: partitioning and topology
BPM'13 Proceedings of the 11th international conference on Business Process Management
DPMine/P: modeling and process mining language and ProM plug-ins
Proceedings of the 9th Central & Eastern European Software Engineering Conference in Russia
Decomposing Petri nets for process mining: A generic approach
Distributed and Parallel Databases
Process Discovery and Conformance Checking Using Passages
Fundamenta Informaticae - Application and Theory of Petri Nets and Concurrency, 2012
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Process discovery--discovering a process model from example behavior recorded in an event log--is one of the most challenging tasks in process mining. Discovery approaches need to deal with competing quality criteria such as fitness, simplicity, precision, and generalization. Moreover, event logs may contain low frequent behavior and tend to be far from complete (i.e., typically only a fraction of the possible behavior is recorded). At the same time, models need to have formal semantics in order to reason about their quality. These complications explain why dozens of process discovery approaches have been proposed in recent years. Most of these approaches are time-consuming and/or produce poor quality models. In fact, simply checking the quality of a model is already computationally challenging. This paper shows that process mining problems can be decomposed into a set of smaller problems after determining the so-called causal structure. Given a causal structure, we partition the activities over a collection of passages. Conformance checking and discovery can be done per passage. The decomposition of the process mining problems has two advantages. First of all, the problem can be distributed over a network of computers. Second, due to the exponential nature of most process mining algorithms, decomposition can significantly reduce computation time (even on a single computer). As a result, conformance checking and process discovery can be done much more efficiently.