Fuzzy Mining - Adaptive Process Simplification Based on Multi-perspective Metrics

By Christian W. Günther, Wil M.P. van der Aalst. International Conference on Business Process Management, 2007

991 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Management Information Systems

View Paper: https://www.semanticscholar.org/paper/a095924208a8dc64ab8e5134cd1579f894a5022e

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Citations in the corpus

Business process analysis in healthcare environments: A methodology based on process mining (2012, methodology): “Trace Clustering and the Fuzzy Miner were then used to separate the regular behavior from the infrequent one, and more understandable process models were discovered for each cluster.”
Process Mining (2016, background): “mance checking approaches use a similar representation [4, 12, 66, 183, 184].”
XES, XESame, and ProM 6 (2010, methodology): “6 shows the fuzzy model that result from running the “Fuzzy miner” [12] on the example log.”
Time prediction based on process mining (2011, background): “More and more information about processes is recorded by information systems in the form of so-called “event logs”.”
On the Role of Fitness, Precision, Generalization and Simplicity in Process Discovery (2012, methodology): “Examples of generalizing algorithms are the fuzzy miner [13] and the heuristics miner [19].”
Discovering Block-Structured Process Models from Event Logs - A Constructive Approach (2013, methodology): “Abstraction-based techniques such as the Fuzzy miner [17] produce models that do not have executable semantics and hence guarantee neither soundness nor fitness nor any kind of rediscoverability.”
Trace Clustering in Process Mining (2008, methodology): “There are some approaches to handle complex process models from real-life process logs, Günther and van der Aalst [5] proposed the fuzzy mining technique that allows for simplifying process models highlighting important flows.”
Process mining in healthcare: A literature review (2016, methodology): “These strate-Table Heuristics Miner [1,14,16,26,33– 35, Fuzzy Miner [1,11,12,14,15,33,37,42,55,56,63,67,73,75,87] 20 Trace Clustering [11,15,35,40,41,44,60,67] 11 Conformance Checker [1,14,40,56,78,80] 8 Performance [11,14,39,42,56,59] 8 Performance Sequence Analyzer [42,44,50,54,84] 7 Ontologies [3”
Process mining techniques for analysing patterns and strategies in students’ self-regulated learning (2013, methodology): “The latter happens if less-significant nodes can be preserved by merging them to a cluster of highly correlated nodes (Günther and van der Aalst 2007).”