Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Conformance checking of processes based on monitoring real behavior
Information Systems
A fresh look at precision in process conformance
BPM'10 Proceedings of the 8th international conference on Business process management
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Satisfiability modulo theories: introduction and applications
Communications of the ACM
Causal nets: a modeling language tailored towards process discovery
CONCUR'11 Proceedings of the 22nd international conference on Concurrency theory
Conformance Checking Using Cost-Based Fitness Analysis
EDOC '11 Proceedings of the 2011 IEEE 15th International Enterprise Distributed Object Computing Conference
ICATPN'05 Proceedings of the 26th international conference on Applications and Theory of Petri Nets
A High-Level Strategy for C-net Discovery
ACSD '12 Proceedings of the 2012 12th International Conference on Application of Concurrency to System Design
An SMT-Based discovery algorithm for c-nets
PETRI NETS'12 Proceedings of the 33rd international conference on Application and Theory of Petri Nets
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As the complexity of information systems evolves, there is a growing interest in defining suitable process models than can overcome the limitations of traditional formalisms like Petri nets or related. Causal nets may be one of such process models, since their declarative semantics and simple graph structure deviates from existing formalisms. Due to their novelty, few discovery algorithms exist for Causal nets. Moreover, the existing ones offer poor guarantees regarding the produced outcome. We describe an algorithm that can be applied as a second step to any discovery technique to improve the quality of the Causal net derived. We have tested the technique in combination with the existing algorithms in the literature, noticing a considerable improvement.