Title :
Workflow Quality of Service Management using Data Mining Techniques
Author_Institution :
Dept. of Math. & Eng., Madeira Univ., Funchal
Abstract :
Organizations have been aware of the importance of quality of service (QoS) for competitiveness for some time. It has been widely recognized that workflow systems are a suitable solution for managing the QoS of processes and workflows. The correct management of the QoS of workflows allows for organizations to increase customer satisfaction, reduce internal costs, and increase added value services. In this paper we show a novel method, composed of several phases, describing how organizations can apply data mining algorithms to predict the QoS for their running workflow instances. Our method has been validated using experimentation by applying different data mining algorithms to predict the QoS of workflow
Keywords :
data mining; quality of service; workflow management software; added value services; business process; customer satisfaction; data mining techniques; quality of service; workflow management; workflow systems; Business process re-engineering; Costs; Customer satisfaction; Data mining; Monitoring; Prediction algorithms; Quality management; Quality of service; Runtime; Workflow management software; Business Process; Data Mining; Quality of Service; Workflow;
Conference_Titel :
Intelligent Systems, 2006 3rd International IEEE Conference on
Conference_Location :
London
Print_ISBN :
1-4244-01996-8
Electronic_ISBN :
1-4244-01996-8
DOI :
10.1109/IS.2006.348466
