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Incremental process discovery

Record Type:	Electronic resources : Monograph/item
Title/Author:	Incremental process discoveryby Daniel Schuster.
Author:	Schuster, Daniel.
Published:	Cham :Springer Nature Switzerland :2025.
Description:	xvi, 367 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Data mining.
Online resource:	https://doi.org/10.1007/978-3-031-80565-3
ISBN:	9783031805653$q(electronic bk.)

Incremental process discovery
Schuster, Daniel.

Incremental process discovery[electronic resource] /by Daniel Schuster. - Cham :Springer Nature Switzerland :2025. - xvi, 367 p. :ill. (some col.), digital ;24 cm. - Lecture notes in business information processing,5401865-1356 ;. - Lecture notes in business information processing ;96..

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

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.

ISBN: 9783031805653$q(electronic bk.)

Standard No.: 10.1007/978-3-031-80565-3doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Incremental process discovery
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