Mastering Organizational Dynamics Using Process Mining (eBook)

Artikelnummer: 978-3-031-93530-5
Einband: PDF
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This book is a revised version of the PhD dissertation written by the author at Queensland University of Technology.

It presents research in the field of process mining, with a focus of developing data-driven methods to discover insights about human resources and their groups in an organizational business process context. It provides an overview on mining organizational models from event logs and introduces a set of novel ideas, framework, and approaches proposed to enhance the state-of-the-art. The book is suitable for researchers and practitioners in the fields of business process management and process mining.

In 2024, the PhD dissertation won the "BPM Dissertation Award", granted to outstanding PhD theses in the field of Business Process Management.

This book is a revised version of the PhD dissertation written by the author at Queensland University of Technology.

It presents research in the field of process mining, with a focus of developing data-driven methods to discover insights about human resources and their groups in an organizational business process context. It provides an overview on mining organizational models from event logs and introduces a set of novel ideas, framework, and approaches proposed to enhance the state-of-the-art. The book is suitable for researchers and practitioners in the fields of business process management and process mining.

In 2024, the PhD dissertation won the "BPM Dissertation Award", granted to outstanding PhD theses in the field of Business Process Management.

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VerlagSpringer Nature Switzerland
EinbandPDF
Erscheinungsjahr2025
Seitenangabe107 S.
AusgabekennzeichenEnglisch
AbbildungenXIV, 107 p. 29 illus.
Masse7'847 KB
PlattformPDF
ReiheLecture Notes in Business Information Processing; Computer Science; Computer Science
AutorYang, Roy Jing

Alle Bände der Reihe "Lecture Notes in Business Information Processing; Computer Science; Computer Science (R0)"

Über den Autor Roy Jing Yang

Jing Roy Yang is a postdoctoral research fellow at Queensland University of Technology (QUT), Australia. His research focuses on discovering knowledge from process execution data to support improved decision-making, especially knowledge about (human) resources, and process automation.

Weitere Titel von Roy Jing Yang

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