fulltext (2) - Process Mining towards Semantics A.K Alves...

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Unformatted text preview: Process Mining towards Semantics A.K. Alves de Medeiros and W.M.P. van der Aalst Eindhoven University of Technology, P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands { a.k.medeiros,w.m.p.v.d.aalst } @tue.nl Abstract. Process mining techniques target the automatic discovery of information about process models in organizations. The discovery is based on the execution data registered in event logs . Current techniques support a variety of practical analysis, but they are somewhat limited because the labels in the log are not linked to any concepts. Thus, in this chapter we show how the analysis provided by current techniques can be improved by including semantic data in event logs. Our explanation is divided into two main parts. The first part illustrates the power of current process mining techniques by showing how to use the open source process mining tool ProM to answer concrete questions that managers typically have about business processes. The second part utilizes usage scenarios to motivate how process mining techniques could benefit from semantic annotated event logs and defines a concrete semantic log format for ProM. The ProM tool is available at www.processmining.org. 1 Introduction Nowadays, most organizations use information systems to support the execu- tion of their business processes [21]. Examples of information systems support- ing operational processes are Workflow Management Systems (WMS) [10,15], Customer Relationship Management (CRM) systems, Enterprise Resource Plan- ning (ERP) systems and so on. These information systems may contain an ex- plicit model of the processes (for instance, workflow systems like Staffware [8], COSA [1], etc.), may support the tasks involved in the process without neces- sarily defining an explicit process model (for instance, ERP systems like SAP R/3 [6]), or may simply keep track (for auditing purposes) of the tasks that have been performed without providing any support for the actual execution of those tasks (for instance, custom-made information systems in hospitals). Either way, these information systems typically support logging capabilities that reg- ister what has been executed in the organization. These produced logs usually contain data about cases (i.e. process instances) that have been executed in the organization, the times at which the tasks were executed, the persons or systems that performed these tasks, and other kinds of data. These logs are the starting point for process mining, and are usually called event logs . For instance, con- sider the event log in Table 1. This log contains information about four process instances (cases) of a process that handles fines. Process mining targets the automatic discovery of information from an event log. This discovered information can be used to deploy new systems that support T.S. Dillon et al. (Eds.): Advances in Web Semantics I, LNCS 4891, pp. 35–80, 2008....
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This note was uploaded on 01/27/2011 for the course PHI 365 taught by Professor Spector during the Spring '10 term at SUNY Stony Brook.

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fulltext (2) - Process Mining towards Semantics A.K Alves...

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