DocumentCode :
1041210
Title :
Workflow mining: discovering process models from event logs
Author :
van der Aalst, Wil ; Weijters, Ton ; Maruster, Laura
Author_Institution :
Dept. of Technol. Manage., Eindhoven Univ. of Technol., Netherlands
Volume :
16
Issue :
9
fYear :
2004
Firstpage :
1128
Lastpage :
1142
Abstract :
Contemporary workflow management systems are driven by explicit process models, i.e., a completely specified workflow design is required in order to enact a given workflow process. Creating a workflow design is a complicated time-consuming process and, typically, there are discrepancies between the actual workflow processes and the processes as perceived by the management. Therefore, we have developed techniques for discovering workflow models. The starting point for such techniques is a so-called "workflow log" containing information about the workflow process as it is actually being executed. We present a new algorithm to extract a process model from such a log and represent it in terms of a Petri net. However, we also demonstrate that it is not possible to discover arbitrary workflow processes. We explore a class of workflow processes that can be discovered. We show that the α-algorithm can successfully mine any workflow represented by a so-called SWF-net.
Keywords :
Petri nets; data mining; workflow management software; α-algorithm; Petri net; SWF-net; event logs; process models; time-consuming process; workflow design; workflow log; workflow management systems; workflow mining; Customer relationship management; Data mining; Enterprise resource planning; Isolation technology; Management information systems; Petri nets; Routing; Software systems; Technology management; Workflow management software; 65; Index Terms- Workflow mining; Petri nets.; data mining; workflow management;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2004.47
Filename :
1316839
Link To Document :
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