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Incremental process discovery
~
Schuster, Daniel.
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Incremental process discovery
Record Type:
Electronic resources : Monograph/item
Title/Author:
Incremental process discovery/ by Daniel Schuster.
Author:
Schuster, Daniel.
Published:
Cham :Springer Nature Switzerland : : 2025.,
Description:
xvi, 367 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
Opening and fundamentals -- incremental process discovery -- facilitating interaction with event data -- realization and application -- closure.
Contained By:
Springer Nature eBook
Subject:
Business Process Management. -
Online resource:
https://doi.org/10.1007/978-3-031-80565-3
ISBN:
9783031805653
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 ;540..
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
Standard No.: 10.1007/978-3-031-80565-3doiSubjects--Topical Terms:
2134548
Business Process Management.
LC Class. No.: QA76.9.D343
Dewey Class. No.: 006.312
Incremental process discovery
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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.
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Computer Science (SpringerNature-11645)
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W9515154
電子資源
11.線上閱覽_V
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EB QA76.9.D343
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