Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Discovering Workflow Performance Models from Timed Logs
EDCIS '02 Proceedings of the First International Conference on Engineering and Deployment of Cooperative Information Systems
Policy resolution for workflow management systems
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A machine learning approach to semi-automating workflow staff assignment
Proceedings of the 2007 ACM symposium on Applied computing
Capturing business benefits from process improvement: four fallacies and what to do about them
Proceedings of the 1st international workshop on Business impact of process improvements
Agent Assignment for Process Management: Pattern Based Agent Performance Evaluation
Agents and Data Mining Interaction
ICATPN'05 Proceedings of the 26th international conference on Applications and Theory of Petri Nets
Mining staff assignment rules from event-based data
BPM'05 Proceedings of the Third international conference on Business Process Management
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Workflow Management Systems not only need to provide a mechanism to represent the organizational elements involved during the execution of workflow processes but they also must provide the mechanism for continuous improvements within these elements. But, in almost, all workflow management systems the role concept is determined once at the introduction of a workflow application and is not reevaluated to observe how successfully certain processes are performed by the authorized agents. This paper describes an approach which evaluates whether agents assigned to a process are working successfully and feed this information back for future agent assignments promising best business benefit for the enterprise. The approach is called Agent Performance Evaluation (APE) and is based on data mining technique combined with post processing technique.