The Data Preprocessing of Behavior Pattern Discovering in Collaboration Environment
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
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This paper conceives a workcase classification method and implements it as a tool so as to be used in workflow mining systems. The method is for resolving the workcase classification problem issued for mining an activity firing or execution sequence of a workcase from monitoring and audit logs. That is, it finally generates a workcase classification decision tree consisting of a minimal set of critical activities to be used for deciding the corresponding researchable-path of the workcases. Why is the methodefficient? Because it uses a minimal decision tree in classifying workcasesý reachable-paths. And the tool is a graphical visualizer of the method, and consists of three subsystems used to automatically generate information control net, activity dependency net and minimal activity net through their corresponding algorithms. Especially the method and tool might be an impeccable solution for the specific domain of massively parallel large-scale workflow procedures. In a consequence, workflow mining methodologies and systems are rapidly growing and coping with a wide diversity of domains in terms of their applications and working environments. So, the literature needs various, advanced, and specialized workflow mining techniques and architectures that are used for finally feed-backing their analysis results to the redesign and reengineering phase of the existing workflow and business process models. We strongly believe that this work might be one of those impeccable attempts and pioneering contributions for pioneering and advancing the workflow mining technology.