Titlebook: Data-Driven Process Discovery and Analysis; 8th IFIP WG 2.6 Inte Paolo Ceravolo,Maurice van Keulen,María Teresa Góm Conference proceedings

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書(shū)目名稱Data-Driven Process Discovery and Analysis影響因子(影響力)




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General Model for Tracking Manufacturing Products Using Graph Databases,pplied and mixed to a certain degree during an indeterminate number of stages, what makes it very difficult to trace each of these parts from its origin to its presence in a final product. In order to overcome this limitation, we have worked towards the design of a general solution aiming to improve

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Pau Luque,Ismael Martínez Torrestion of time is spent actually applying techniques to discover, control and predict the business process. Moreover, current process mining techniques assume a . case notion. However, in real-life processes often different case notions are intertwined. For example, events of the same order handling p

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Jorge Luis Fabra-Zamora,Gonzalo Villa Rosase optimized, despite heterogeneous nature of these data structures. This data may also be used for various types of analysis, such as reasoning, process querying and process mining, which consume different data formats. However, all these structures and formats share a common ground: the business-pr