collaborators

5 papers

cs.AI2025

Discriminative Rule Learning for Outcome-Guided Process Model Discovery

Ali Norouzifar, Wil van der Aalst

Event logs extracted from information systems offer a rich foundation for understanding and improving business processes. In many real-world applications, it is possible to disting…

cs.AI2025

Integrating Domain Knowledge into Process Discovery Using Large Language Models

Ali Norouzifar, Humam Kourani, Marcus Dees +1

Process discovery aims to derive process models from event logs, providing insights into operational behavior and forming a foundation for conformance checking and process improvem…

cs.FL2024

Imposing Rules in Process Discovery: an Inductive Mining Approach

Ali Norouzifar, Marcus Dees, Wil van der Aalst

Process discovery aims to discover descriptive process models from event logs. These discovered process models depict the actual execution of a process and serve as a foundational…

cs.AI2024

Bridging Domain Knowledge and Process Discovery Using Large Language Models

Ali Norouzifar, Humam Kourani, Marcus Dees +1

Discovering good process models is essential for different process analysis tasks such as conformance checking and process improvements. Automated process discovery methods often o…

cs.SE2024

Process Variant Analysis Across Continuous Features: A Novel Framework

Ali Norouzifar, Majid Rafiei, Marcus Dees +1

Extracted event data from information systems often contain a variety of process executions making the data complex and difficult to comprehend. Unlike current research which only…