Overlapping Analytic Stages in Online Process Mining

Gabriel Marques Tavares · Paolo Ceravolo · Victor G. Turrisi da Costa · Ernesto Damiani · Sylvio Barbon

33 citations0/0 files storedIEEE International Conference on Services Computing

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

Abstract

Process mining uses business event logs to understand the flow of activities, to identify anomalous cases and to enhance processes. Today, real-time process mining tools mainly deal with a single task at a time (process discovery, conformance checking, process enhancement or concept change detection). In this paper, we introduce an underlined layer overlapping with multiple online process mining tasks to smooth their integration. Following a case clustering approach, based on trace and time analysis, our proposal supports simultaneously?: process discovery, conformance checking, and concept drift detection. We evaluated our approach and compared it with other techniques using both real-life and synthetic data, obtaining promising results.

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References

2011Process Mining 2011Process Mining: Discovery, Conformance and Enhancement of Business Processes 2010Similarity of business process models: Metrics and evaluation 2003Rediscovering workflow models from event-based data using little thumb 2004Business Process Management Demystified: A Tutorial on Models, Systems and Standards for Workflow Management 2013Dealing With Concept Drifts in Process Mining 2009Anomaly Detection Using Process Mining 2015Fast and Accurate Business Process Drift Detection

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2024Tuning Machine Learning to Address Process Mining Requirements 2024Survey and Benchmark of Anomaly Detection in Business Processes 2020Analysis of Language Inspired Trace Representation for Anomaly Detection

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