Workflow Quality of Service Management using Data Mining Techniques

Author

Cardoso, Jorge

Author_Institution

Dept. of Math. & Eng., Madeira Univ., Funchal

fYear

2006

fDate

Sept. 2006

Firstpage

479

Lastpage

482

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IS.2006.348466

Filename

4155473