Sommers, D. (Accepted/In press). Illuminating Perspectives of Deviations in Process Behavior. [Phd Thesis 1 (Research TU/e / Graduation TU/e), Mathematics and Computer Science]. Eindhoven University of Technology.
Mozafari Mehr, A. S. (2024). Multi-perspective Conformance Checking: Identifying and Understanding Patterns of Anomalous Behavior. [Phd Thesis 1 (Research TU/e / Graduation TU/e), Mathematics and Computer Science]. Eindhoven University of Technology. Summary The problem of anomaly detection in business process executions has high level of complexity. On one hand, detecting deviating behavior requires considering various Read More …
Syamsiyah, A. (2020). In-database preprocessing for process mining. Technische Universiteit Eindhoven.
Dixit, P. A. M. (2019). Interactive process mining Eindhoven: Technische Universiteit Eindhoven
Tax, N. (2019). Mining insights from weakly-structured event data Eindhoven: Technische Universiteit Eindhoven
Li, G. (2019). Process mining based on object-centric behavioral constraint (OCBC) models Eindhoven
Gonzalez Lopez de Murillas, E. (2019). Process mining on databases: extracting event data from real-life data sources Eindhoven: Technische Universiteit Eindhoven
van Zelst, S. J. (2019). Process mining with streaming data Eindhoven: Technische Universiteit Eindhoven
Liu, C. (2019). Software data analytics: architectural model discovery and design pattern detection Eindhoven: Technische Universiteit Eindhoven
Leemans, M. (2018). Hierarchical process mining for scalable software analysis. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: Wil van der Aalst & Mark van den Brand).
Mannhardt, F. (2018). Multi-perspective process mining. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: Hajo Reijers, Wil van der Aalst & Massimiliano de Leoni).
Lu, X. (2018). Using behavioral context in process mining : exploration, preprocessing and analysis of event data. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: Wil van der Aalst, Dirk Fahland & Nicola Zannone)
Kalenkova, A.A. (2018). Learning high-level process models from event data. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: Wil van der Aalst & Irina Lomazova).
