Table of Contents

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   Book Overview
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   Chapter 1 Do You Behave Always the Same?
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   Chapter 2 Enhancing Data-Awareness of Object-Centric Event Logs
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   Chapter 3 Multi-perspective Identification of Event Groups for Event Abstraction
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   Chapter 4 Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach
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   Chapter 5 A Survey on the Application of Process Mining to Smart Spaces Data
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   Chapter 6 Building User Journey Games from Multi-party Event Logs
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   Chapter 7 Leveraging Event Data for Measuring Process Complexity
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   Chapter 8 Discrimination-Aware Process Mining: A Discussion
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    Chapter 9 TraVaS: Differentially Private Trace Variant Selection for Process Mining
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    Chapter 10 BERMUDA: Participatory Mapping of Domain Activities to Event Data via System Interfaces
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    Chapter 11 Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings
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    Chapter 12 Uncovering Change: A Streaming Approach for Declarative Processes
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    Chapter 13 Deep Reinforcement Learning for Resource Allocation in Business Processes
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    Chapter 14 On the Potential of Textual Data for Explainable Predictive Process Monitoring
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    Chapter 15 Attribute-Based Conformance Diagnosis: Correlating Trace Attributes with Process Conformance
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    Chapter 16 Detecting Surprising Situations in Event Data
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    Chapter 17 LSTM-Based Anomaly Detection of Process Instances: Benchmark and Tweaks
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    Chapter 18 Genetic Algorithms for AutoML in Process Predictive Monitoring
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    Chapter 19 Outcome-Oriented Predictive Process Monitoring on Positive and Unlabelled Event Logs
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    Chapter 20 Clustering Analysis and Frequent Pattern Mining for Process Profile Analysis: An Exploratory Study for Object-Centric Event Logs
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    Chapter 21 Weighted Violations in Alignment-Based Conformance Checking
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    Chapter 22 Event Log Generation in MIMIC-IV Research Paper
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    Chapter 23 Process Modeling and Conformance Checking in Healthcare: A COVID-19 Case Study
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    Chapter 24 SAMPLE: A Semantic Approach for Multi-perspective Event Log Generation
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    Chapter 25 Research Paper: Process Mining and Synthetic Health Data: Reflections and Lessons Learnt
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    Chapter 26 Discovering Break Behaviours in Process Mining: An Application to Discover Treatment Pathways in ICU of Patients with Acute Coronary Syndrome
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    Chapter 27 Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study
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    Chapter 28 Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction
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    Chapter 29 Measuring the Impact of COVID-19 on Hospital Care Pathways
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    Chapter 30 Deriving Event Logs from Legacy Software Systems
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    Chapter 31 Defining Data Quality Issues in Process Mining with IoT Data
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    Chapter 32 Creating Translucent Event Logs to Improve Process Discovery
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    Chapter 33 SAP Signavio Academic Models: A Large Process Model Dataset
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    Chapter 34 A Virtual Knowledge Graph Based Approach for Object-Centric Event Logs Extraction
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    Chapter 35 Monitoring Constraints in Business Processes Using Object-Centric Constraint Graphs
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    Chapter 36 Aggregating Event Knowledge Graphs for Task Analysis
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    Chapter 37 A Combined Approach of Process Mining and Rule-Based AI for Study Planning and Monitoring in Higher Education
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    Chapter 38 Identifying the Steps in an Exploratory Data Analysis: A Process-Oriented Approach
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    Chapter 39 Discovering Students’ Learning Strategies in a Visual Programming MOOC Through Process Mining Techniques
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    Chapter 40 Domain-Driven Event Abstraction Framework for Learning Dynamics in MOOCs Sessions
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    Chapter 41 Process Mining for Analyzing Open Questions Computer-Aided Examinations
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    Chapter 42 Process Mining on Curriculum-Based Study Data: A Case Study at a German University