Communications of the ACM
Supporting Flexible Processes through Recommendations Based on History
BPM '08 Proceedings of the 6th International Conference on Business Process Management
Workflow simulation for operational decision support
Data & Knowledge Engineering
Coloured Petri Nets: Modelling and Validation of Concurrent Systems
Coloured Petri Nets: Modelling and Validation of Concurrent Systems
Beyond process mining: from the past to present and future
CAiSE'10 Proceedings of the 22nd international conference on Advanced information systems engineering
Time prediction based on process mining
Information Systems
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Modeling and verification of a protocol for operational support using coloured petri nets
PETRI NETS'11 Proceedings of the 32nd international conference on Applications and theory of Petri Nets
Access/CPN 2.0: a high-level interface to coloured petri net models
PETRI NETS'11 Proceedings of the 32nd international conference on Applications and theory of Petri Nets
Supporting risk-informed decisions during business process execution
CAiSE'13 Proceedings of the 25th international conference on Advanced Information Systems Engineering
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Operational support is a specific type of process mining that assists users while process instances are being executed. Examples are predicting the remaining processing time of a running insurance claim and recommending the action that minimizes the treatment costs of a particular patient. Whereas it is easy to evaluate prediction techniques using cross validation, the evaluation of recommendation techniques is challenging as the recommender influences the execution of the process. It is therefore impossible to simply use historic event data. Therefore, we present an approach where we use a colored Petri net model of user behavior to drive a real workflow system and real implementations of operational support, thereby providing a way of evaluating algorithms for operational support before implementation and a costly test using real users. In this paper, we evaluate algorithms for operational support using different user models. We have implemented our approach using Access/CPN 2.0.