3 citations · 3 across the 3 of their papers we have counts for
3 papers
Problem-oriented AutoML in Clustering
Matheus Camilo da Silva, Gabriel Marques Tavares, Eric Medvet +1
The Problem-oriented AutoML in Clustering (PoAC) framework introduces a novel, flexible approach to automating clustering tasks by addressing the shortcomings of traditional AutoML…
Selecting Optimal Trace Clustering Pipelines with AutoML
Sylvio Barbon, Paolo Ceravolo, Ernesto Damiani +1
Trace clustering has been extensively used to preprocess event logs. By grouping similar behavior, these techniques guide the identification of sub-logs, producing more understanda…
Using Meta-learning to Recommend Process Discovery Methods
Sylvio Barbon, Paolo Ceravolo, Ernesto Damiani +1
Process discovery methods have obtained remarkable achievements in Process Mining, delivering comprehensible process models to enhance management capabilities. However, selecting t…