Process Mining Put into Context

Wil M. P. van der Aalst · Schahram Dustdar

124 citations0/0 files storedIEEE Internet Computing

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Business Process Modeling and Analysis Data Mining Algorithms and Applications Robotic Process Automation Applications

Abstract

Process mining techniques help organizations discover and analyze business processes based on raw event data. The recently released "Process Mining Manifesto" presents guiding principles and challenges for process mining. Here, the authors summarize the manifesto's main points and argue that analysts should take into account the context in which events occur when analyzing processes.

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References

2004Workflow mining: discovering process models from event logs 2011Process Mining 2011Process Mining: Discovery, Conformance and Enhancement of Business Processes 2012Process Mining Manifesto 2008Contextualisation of business processes 2011Handling Concept Drift in Process Mining

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2015Queue mining for delay prediction in multi-class service processes 2013Process Cubes: Slicing, Dicing, Rolling Up and Drilling Down Event Data for Process Mining 2014Business Process Simulation Survival Guide 2013Root Cause Analysis with Enriched Process Logs 2014A General Framework for Correlating Business Process Characteristics 2020Process Mining for Six Sigma 2020Bringing Context Inside Process Research with Digital Trace Data 2015Comparative Process Mining in Education: An Approach Based on Process Cubes

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