Incremental Process Discovery

Daniel Schuster

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English

Springer International Publishing AG
06 April 2025

Social research & statistics; Business mathematics & systems; Computing: general

Series: Lecture Notes in Business Information Processing

This book constitutes the revised version of the award-winning PhD dissertation written by the author at RWTH Aachen, Germany.

It presents a framework for incremental process discovery that allows users to learn and refine process models from event data iteratively. Next to process discovery and event data handling, it also contributes to conformance checking, a further fundamental process mining task. Eventually, it presents Cortado, an open-source process mining software tool that implements the algorithms and techniques proposed in an integrated and comprehensive fashion. This part also includes a case study applying Cortado and, therefore, the various contributions of this thesis in a real-life scenario.

In 2024, this PhD dissertation won the “Best Process Mining PhD Dissertation Award” by the IEEE Task Force for Process Mining, granted to outstanding PhD theses in this field.

By: Daniel Schuster
Imprint: Springer International Publishing AG
Country of Publication: Switzerland
Volume: 540
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9783031805646
ISBN 10: 303180564X
Series: Lecture Notes in Business Information Processing
Pages: 367
Publication Date: 06 April 2025
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Opening and fundamentals.- incremental process discovery.- facilitating interaction with event data.- realization and application.- closure.