| Convolutional autoencoder-based SOH estimation of lithium-ion batteries using electrochemical impedance spectroscopy J Obregon, YR Han, CW Ho, D Mouraliraman, CW Lee, JY Jung Journal of Energy Storage 60, 106680, 2023 | 65 | 2023 |
| RuleCOSI: Combination and simplification of production rules from boosted decision trees for imbalanced classification J Obregon, A Kim, JY Jung Expert Systems with Applications 126, 64-82, 2019 | 40 | 2019 |
| Rule-based explanations based on ensemble machine learning for detecting sink mark defects in the injection moulding process J Obregon, J Hong, JY Jung Journal of Manufacturing Systems 60, 392-405, 2021 | 39 | 2021 |
| Constructing decision trees from process logs for performer recommendation A Kim, J Obregon, JY Jung Business Process Management Workshops: BPM 2013 International Workshops …, 2014 | 33 | 2014 |
| Decision mining in a broader context: An overview of the current landscape and future directions J De Smedt, SKLM vanden Broucke, J Obregon, A Kim, JY Jung, ... Business Process Management Workshops: BPM 2016 International Workshops, Rio …, 2017 | 25 | 2017 |
| RuleCOSI+: Rule extraction for interpreting classification tree ensembles J Obregon, JY Jung Information Fusion 89, 355-381, 2023 | 20 | 2023 |
| InfoFlow: Mining information flow based on user community in social networking services J Obregon, M Song, JY Jung IEEE Access 7, 48024-48036, 2019 | 11 | 2019 |
| Analyzing information flow and context for facebook fan pages K Kim, J Obregon, JY Jung IEICE TRANSACTIONS on Information and Systems 97 (4), 811-814, 2014 | 8 | 2014 |
| PRANAS: A process analytics system based on process warehouse and cube for supply chain management A Kim, J Obregon, JY Jung Applied Sciences 10 (10), 3521, 2020 | 7 | 2020 |
| DTMiner: A tool for decision making based on historical process data J Obregon, A Kim, JY Jung Asia Pacific Business Process Management: First Asia Pacific Conference, AP …, 2013 | 7 | 2013 |
| Multi-step photovoltaic power forecasting using transformer and recurrent neural networks J Kim, J Obregon, H Park, JY Jung Renewable and Sustainable Energy Reviews 200, 114479, 2024 | 5 | 2024 |
| Rule-based visualization of faulty process conditions in the die-casting manufacturing J Obregon, JY Jung Journal of Intelligent Manufacturing 35 (2), 521-537, 2024 | 4 | 2024 |
| Explanation of ensemble models J Obregon, JY Jung Human-Centered Artificial Intelligence, 51-72, 2022 | 4 | 2022 |
| Conversion of Natural Biowaste into Energy Storage Materials and Estimation of Discharge Capacity through Transfer Learning in Li-Ion Batteries M Nanthagopal, D Mouraliraman, YR Han, CW Ho, J Obregon, JY Jung, ... Nanomaterials 13 (22), 2963, 2023 | 1 | 2023 |
| Interpretable machine learning for fault detection using manufacturing data J Obregon, D Park, J Hong, JY Jung 대한산업공학회 추계학술대회 논문집, 110-133, 2019 | 1 | 2019 |
| Discovering users-centric hierarchical process models in social networking services J Obregon, JY Jung 대한산업공학회 추계학술대회 논문집, 480-489, 2014 | 1 | 2014 |
| Stacking Predictive Models into LLMs: Improving Transparency in Manufacturing Quality Predictions J Obregon 대한산업공학회 추계학술대회 논문집, 429-436, 2024 | | 2024 |
| Special Issue on “Application of Big Data Analysis and Advanced Analytics in Sustainable Production Process” S Hur, JY Jung, J Obregon Processes 10 (4), 670, 2022 | | 2022 |
| Extracting Simplified Rules from Ensemble Decision Trees J Obregon, A Kim, JY Jung 한국 EA 학회 학술발표논문집, 277-282, 2018 | | 2018 |
| Decision Points Analysis in Business Process using Process Mining: An Exportation Consultancy Service Company Case: An Exportation Consultancy Service Company Case J Obregon, B Carrera, JY Jung 한국경영과학회 학술대회논문집, 4243-4254, 2016 | | 2016 |
