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• W2146567607 abstract "Increasingly, devices are connected to the Internet and are recording events. Computers, X-ray machines, high-end copiers, interactive kiosks, RFID scanners, etc. are examples of such devices. Typically, there are many devices running the same application (e.g., a computer running SAP R/3 or an X-ray machine running diagnosis software) and their event logs reflect the actual use of the application in the field. This way it is possible to systematically monitor real-life processes. Process mining aims at the analysis of such event logs, and we argue that proper log analysis can be used to increase reliability, usability, and serviceability of deployed applications. In this paper, we present a case study conducted within Philips Healthcare and based on the process mining tool ProM. Moreover, we address technical challenges of dealing with large, real-life data sets, and discuss generic methods of dealing with problems of diversity and complexity in unstructured environments." @default.
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• W2146567607 date "2008-01-01" @default.
• W2146567607 modified "2023-09-26" @default.
• W2146567607 title "Monitoring deployed application usage with process mining" @default.
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