Outcome-oriented predictive process monitoring: review and benchmark I Teinemaa, M Dumas, M La Rosa, FM Maggi ACM Transactions on Knowledge Discovery in Data 13 (2), 17:1-17:57, 2019 | 372 | 2019 |
Clustering-based predictive process monitoring C Di Francescomarino, M Dumas, FM Maggi, I Teinemaa IEEE transactions on services computing 12 (6), 896-909, 2016 | 211 | 2016 |
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring I Verenich, M Dumas, ML Rosa, FM Maggi, I Teinemaa ACM Transactions on Intelligent Systems and Technology (TIST) 10 (4), 1-34, 2019 | 209 | 2019 |
Predictive business process monitoring with structured and unstructured data I Teinemaa, M Dumas, FM Maggi, C Di Francescomarino Business Process Management: 14th International Conference, BPM 2016, Rio de …, 2016 | 134 | 2016 |
Process mining meets causal machine learning: Discovering causal rules from event logs ZD Bozorgi, I Teinemaa, M Dumas, M La Rosa, A Polyvyanyy 2020 2nd International Conference on Process Mining (ICPM), 129-136, 2020 | 72 | 2020 |
An interdisciplinary comparison of sequence modeling methods for next-element prediction N Tax, I Teinemaa, SJ van Zelst Software and Systems Modeling 19 (6), 1345-1365, 2020 | 67 | 2020 |
Semantics and analysis of DMN decision tables D Calvanese, M Dumas, Ü Laurson, FM Maggi, M Montali, I Teinemaa Business Process Management: 14th International Conference, BPM 2016, Rio de …, 2016 | 64 | 2016 |
Temporal Stability in Predictive Process Monitoring I Teinemaa, M Dumas, A Leontjeva, FM Maggi Data Mining and Knowledge Discovery 32 (5), 1306–1338, 2018 | 63 | 2018 |
Alarm-Based Prescriptive Process Monitoring I Teinemaa, N Tax, M de Leoni, M Dumas, FM Maggi International Conference on Business Process Management 329, 91-107, 2018 | 60 | 2018 |
Semantics, analysis and simplification of DMN decision tables D Calvanese, M Dumas, Ü Laurson, FM Maggi, M Montali, I Teinemaa Information Systems 78, 112-125, 2018 | 57 | 2018 |
Fire now, fire later: alarm-based systems for prescriptive process monitoring SA Fahrenkrog-Petersen, N Tax, I Teinemaa, M Dumas, M Leoni, ... Knowledge and Information Systems 64 (2), 559-587, 2022 | 56 | 2022 |
Prescriptive process monitoring for cost-aware cycle time reduction ZD Bozorgi, I Teinemaa, M Dumas, M La Rosa, A Polyvyanyy 2021 3rd international conference on process mining (ICPM), 96-103, 2021 | 54 | 2021 |
Personalization in practice: Methods and applications D Goldenberg, K Kofman, J Albert, S Mizrachi, A Horowitz, I Teinemaa Proceedings of the 14th ACM international conference on web search and data …, 2021 | 53 | 2021 |
Encoding resource experience for predictive process monitoring J Kim, M Comuzzi, M Dumas, FM Maggi, I Teinemaa Decision Support Systems 153, 113669, 2022 | 32 | 2022 |
Prescriptive process monitoring based on causal effect estimation ZD Bozorgi, I Teinemaa, M Dumas, M La Rosa, A Polyvyanyy Information Systems 116, 102198, 2023 | 21 | 2023 |
BPIC 2015: Diagnostics of building permit application process in dutch municipalities I Teinemaa, A Leontjeva, KO Masing BPI Challenge Report 72, 2015 | 18 | 2015 |
An experimental evaluation of the generalizing capabilities of process discovery techniques and black-box sequence models N Tax, SJ van Zelst, I Teinemaa Enterprise, Business-Process and Information Systems Modeling: 19th …, 2018 | 14 | 2018 |
A ProM Operational Support Provider for Predictive Monitoring of Business Processes. M Federici, W Rizzi, C Di Francescomarino, M Dumas, C Ghidini, ... BPM (Demos), 1-5, 2015 | 12 | 2015 |
Learning when to treat business processes: Prescriptive process monitoring with causal inference and reinforcement learning ZD Bozorgi, M Dumas, ML Rosa, A Polyvyanyy, M Shoush, I Teinemaa International Conference on Advanced Information Systems Engineering, 364-380, 2023 | 10 | 2023 |
Predictive and Prescriptive Monitoring of Business Process Outcomes. I Teinemaa, B Depaire BPM (PhD/Demos), 15-19, 2019 | 8 | 2019 |