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Grohmann, Nico: Fundamental Data Mining Techniques for Declarative Process Mining. 2022
Inhalt
Preface
Acknowledgements
Contents
List of Figures
List of Tables
Introduction
Motivation
Research Objectives
Thesis Structure
Foundations
Digitalization of Companies
Assessing Digital Maturity
A Comprehensive Digitalization Check
Processes as a Digital Dimension
Business Process Management and Process Mining
The Horus Method
Imperative Process Modeling
Declarative Process Modeling
Multi-perspective Declarative Constraints
Process Mining
History and Foundations
Event Data
Process Discovery
Declarative Process Mining
Application in Practice
Data Mining Techniques for Pattern Discovery
Association Rule Mining
Apriori
FP-Growth
Association Rule Generation
Sequential Pattern Mining
Generalized Sequential Pattern Mining (GSP)
Sequential Rule Mining
Combining Data and Process Mining
Applying Pattern and Rule Mining on Process Event Data
General Setup of the Implementation
Translating Association Rules to DeclareConstraints
Sequential Pattern Mining on Event Logs
Translating Sequential Patterns to SequentialRules
Translating Sequential Patterns or Rules toDeclare Constraints
Evaluation
Evaluation Method
Application on Sample Event Data
Compensation Request Process
Production Process
Purchase Order Process of Production Firm
Overall Evaluation Results Discussion
Related Research and Conclusions
Related Work
Prior Work on Declarative Process Discovery
Multi-perspective Declarative Process Modeling and Mining
Related Research for Declarative Process Modeling and Mining
Conclusions
Summary and Implications
Integration into the Horus Method
Outlook
Bibliography
List of Web Pages
List of Abbreviations
Overview of the Declare Template Set