Process Discovery: Capturing the Invisible

被引:50
作者
van der Aalst, Wil M. P. [1 ]
机构
[1] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands
关键词
PROCESS MODELS; PETRI NETS; IDENTIFICATION;
D O I
10.1109/MCI.2009.935307
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Processes are everywhere. Organizations have business processes to manufacture products, provide services, purchase goods, handle applications, etc. Also in our daily lives we are involved in a variety of processes, for example when we use our car or when we book a trip via the Internet. Although such operational processes are omnipresent, they are at the same time intangible. Unlike a product or a piece of data, processes are less concrete because of their dynamic nature. However, more and more information about these processes is captured in the form of event logs. Contemporary systems ranging from copiers and medical devices to enterprise information systems and cloud infrastructures record events. These events can be used to make processes visible. Using process mining techniques it is possible to discover processes. This provides the insights necessary to manage, control, and improve processes. Process mining has been successfully applied in a variety of domains ranging from healthcare and e-business to high-tech systems and auditing. Despite these successes, there are still many challenges as process discovery shows that the real processes are more "spaghetti-like" than people like to think. It is still very difficult to capture the complex reality in a suitable model. Given the nature of these challenges, techniques originating from Computational Intelligence may assist in the discovery of complex processes.
引用
收藏
页码:28 / 41
页数:14
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