Towards Proximity Graph Auto-configuration: An Approach Based on Meta-learning. - Rafael Seidi Oyamada; Larissa Capobianco Shimomura; Sylvio Barbon Junior; Daniel S. Kaster (ADBIS, 2020)

A survey on graph-based methods for similarity searches in metric spaces. - Larissa Capobianco Shimomura; Rafael Seidi Oyamada; Marcos R. Vieira; Daniel S. Kaster (Inf. Syst., 2021)

A Scikit-learn Extension Dedicated to Process Mining Purposes. - Rafael Seidi Oyamada; Gabriel Marques Tavares; Sylvio Barbon Junior; Paolo Ceravolo (CoopIS (Demos), 2023)

FEEED: Feature Extraction from Event Data. - Andrea Maldonado 001; Gabriel Marques Tavares; Rafael Seidi Oyamada; Paolo Ceravolo; Thomas Seidl 001 (ICPM Doctoral Consortium / Demo, 2023)

The Dataset-Similarity-Based Approach to Select Datasets for Evaluation in Similarity Retrieval. - Matheus A. L. Matiazzo; Vitor de Castro-Silva; Rafael Seidi Oyamada; Daniel S. Kaster (SISAP, 2023)

CoSMo: a Framework for Implementing Conditioned Process Simulation Models. - Rafael Seidi Oyamada; Gabriel M. Tavares; Paolo Ceravolo (CoRR, 2023)

A meta-learning configuration framework for graph-based similarity search indexes. - Rafael Seidi Oyamada; Larissa Capobianco Shimomura; Sylvio Barbon Jr.; Daniel S. Kaster (Inf. Syst., 2023)

Trace encoding in process mining: A survey and benchmarking. - Gabriel M. Tavares; Rafael Seidi Oyamada; Sylvio Barbon; Paolo Ceravolo (Eng. Appl. Artif. Intell., 2023)

CoSMo: A Framework to Instantiate Conditioned Process Simulation Models. - Rafael Seidi Oyamada; Gabriel Marques Tavares; Sylvio Barbon Junior; Paolo Ceravolo (BPM, 2024)

Enhancing Predictive Process Monitoring with Time-Related Feature Engineering. - Rafael Seidi Oyamada; Gabriel Marques Tavares; Sylvio Barbon Junior; Paolo Ceravolo (CAiSE, 2024)