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• W2893723955 abstract "Advances in pervasive computing, sensor networks and activity recognition have opened several paths to achieve novel solutions for applying model-driven data-intensive techniques. Complex system integrating computers, communication and control systems, generate new challenges for Enterprise Systems in the area of data modelling and processing. This paper is focused on the analysis of data intensive streams using process mining techniques, in the context of Enterprise Information Systems. An automated process recognition method based on data acquired from sensor networks, able to generate a process model describing dynamic aspects of the monitored environment, is proposed and analyzed." @default.
• W2893723955 created "2018-10-05" @default.
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• W2893723955 date "2018-09-26" @default.
• W2893723955 modified "2023-10-18" @default.
• W2893723955 title "Automated process recognition architecture for cyber-physical systems" @default.
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• W2893723955 doi "https://doi.org/10.1080/17517575.2018.1521997" @default.
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