Business Process Management Forum: BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
2023
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | Lecture Notes in Business Information Processing Series
v.490 |
| Schlagworte: | |
| Online-Zugang: | DE-2070s |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (423 Seiten) |
| ISBN: | 9783031416231 |
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| 490 | 0 | |a Lecture Notes in Business Information Processing Series |v v.490 | |
| 500 | |a Description based on publisher supplied metadata and other sources | ||
| 505 | 8 | |a Intro -- Preface -- Organization -- Contents -- Foundations -- Trusted Compliance Checking on Blockchain with Commitments: A Model-Driven Approach -- 1 Introduction -- 2 Baseline -- 3 Approach -- 3.1 Identifying On-Chain Information -- 3.2 Generating Smart Contract Code -- 3.3 Deploying Smart Contract Code -- 4 Evaluation -- 5 Related Work -- 6 Conclusion -- References -- The Dpex-Framework: Towards Full WFMS Support for Decentralized Process Execution -- 1 Introduction -- 2 Process Execution in a Workflow Management System -- 3 Process Execution in an Interorganizational Context -- 3.1 Message-Based Collaborations -- 3.2 Decentralized Process Execution: Networking Perspective -- 3.3 Decentralized Process Execution: Security Perspective -- 3.4 Blockchain-Based Process Execution -- 4 Architecture for Decentralized Process Execution -- 4.1 Requirements -- 4.2 Architecture -- 5 Implementation and Use Case -- 5.1 dpex-Library -- 5.2 Implementation in a Real-Life Use Case -- 6 Evaluation of the Architecture -- 7 Discussion of Related Work -- 8 Conclusion and Future Work -- References -- A Reference Data Model to Specify Event Logs for Big Data Pipeline Discovery -- 1 Introduction -- 2 Research Methodology -- 3 Background -- 3.1 Process Mining and Event Logs -- 3.2 Big Data Pipelines -- 3.3 Big Data Pipeline Specification Trough DSLs -- 3.4 Use Case -- 4 Reference Model and XES Extension for Event Logs -- 4.1 Reference Data Model -- 4.2 Extending XES -- 5 Demonstration -- 6 Preliminary Evaluation -- 7 Concluding Remarks -- References -- Foundations of Collaborative DECLARE -- 1 Introduction -- 2 A Bird-Eye-View on LTLf and DECLARE -- 2.1 LTLf -- 2.2 DECLARE -- 3 Collaborative DECLARE -- 3.1 Executing a Collaborative Process -- 3.2 Satisfying the Constraints of a Collaborative Process -- 4 Consistency and Enactment of coDECLARE. | |
| 505 | 8 | |a 4.1 Realizability over Simple Traces -- 4.2 Consistency and Orchestration -- 5 Encoding into LTLf Realizability -- 6 Conclusions -- References -- Declarative Choreographies with Time and Data -- 1 Introduction -- 2 Mixed Timed DCR Choreographies with Data -- 3 Timed DCR Processes with Data and Realizability -- 3.1 Correctness of Realizability -- 3.2 Implementing Synchronous Communication -- 4 Related Work -- 5 Concluding Remarks and Related Work -- References -- Execution Semantics for Process Choreographies with Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Process Choreographies -- 2.2 Interaction Petri Nets -- 3 Motivating Example -- 4 Execution Semantics for Choreographies with Data -- 4.1 Data Exchange Specifications for Choreography Diagrams -- 4.2 Data-Enhanced Interaction Petri Nets -- 4.3 From Choreographies to Data-Enhanced Interaction Petri Nets -- 5 Discussion -- 6 Related Work -- 7 Conclusion -- References -- Large Language Models for Business Process Management: Opportunities and Challenges -- 1 Introduction -- 2 Background -- 2.1 Deep Learning -- 2.2 Large Language Models -- 2.3 Uptake of Large Language Models -- 3 Large Language Models and the BPM Lifecycle -- 3.1 Identification -- 3.2 Discovery -- 3.3 Analysis -- 3.4 Redesign -- 3.5 Implementation -- 3.6 Monitoring -- 4 Research Directions -- 4.1 The Use of Large Language Models in BPM Practice -- 4.2 Usage Guidelines for Researchers and Practitioners -- 4.3 Creation, Release, and Maintenance of Task Variants Specific to BPM -- 4.4 Creation, Release, and Maintenance of Data Sets and Benchmarks -- 4.5 LLM and BPM Artifacts -- 4.6 Development and Release of Large Language Modelss for Business Process Management -- 5 Discussion -- 6 Conclusion -- References -- Engineering -- Predicting Unseen Process Behavior Based on Context Information from Compliance Constraints -- 1 Introduction | |
| 505 | 8 | |a 2 Problem Statement and Preliminaries -- 3 Next Event Label Prediction Approach -- 3.1 Creating the Prediction Model - Offline Component -- 3.2 Next Event Label Prediction - Online Component -- 4 Evaluation -- 4.1 Data Sets -- 4.2 ATS vs. AATS Without Updates -- 4.3 ATS vs. AATS with Updates -- 4.4 AATS vs. Deep-Learning Model Without Updates -- 4.5 AATS vs. Deep-Learning Model with Updates -- 5 Related Work -- 6 Conclusion -- References -- The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them -- 1 Introduction -- 1.1 Motivation -- 1.2 Example -- 1.3 Approach -- 2 Related Work -- 3 Preliminaries -- 4 Method -- 4.1 Detecting High-Level Behavior Using High-Level Events -- 4.2 Connecting High-Level Events -- 4.3 Case Participation in High-Level Behavior -- 5 Evaluation -- 5.1 The BPI Challenge 2017 Event Log -- 5.2 Experimental Setting and General Statistics -- 5.3 Outcome: Success Rate -- 5.4 Throughput Time -- 6 Conclusion -- References -- Adding the Sustainability Dimension in Process Mining Discovery Algorithms Evaluation -- 1 Introduction -- 2 Background and Related Work -- 2.1 Green BPM -- 2.2 Green Process Mining -- 2.3 Automated Process Discovery Benchmark -- 3 Evaluation -- 3.1 SetUp and Methodology -- 3.2 Benchmark Extension -- 3.3 Results -- 4 Discussion -- 5 Conclusions -- References -- Steady State Estimation for Business Process Simulations -- 1 Introduction -- 2 Related Work -- 3 Running Example -- 4 Preliminaries -- 5 Approach -- 5.1 Event Log Completion -- 5.2 Steady-State Estimation -- 5.3 State Loader -- 6 Evaluation -- 6.1 Real-World Event Log -- 6.2 Running Example Event Log -- 6.3 Discussion -- 7 Conclusion -- References -- Analytics Pipeline for Process Mining on Video Data -- 1 Introduction -- 2 Process Analytics Pipeline -- 2.1 Dataset Preparation -- 2.2 Object Tracking | |
| 505 | 8 | |a 2.3 Activity Recognition -- 2.4 Event Abstraction -- 2.5 Case Correlation -- 2.6 Process Mining -- 3 Implementation -- 4 Use Case -- 5 Evaluation -- 5.1 Pre-Processing -- 5.2 Event Log Preparation -- 5.3 Result Stability -- 5.4 Result Meaningfulness -- 5.5 Reproducibility and Data Availability -- 6 Related Work -- 7 Conclusion -- References -- An SQL-Based Declarative Process Mining Framework for Analyzing Process Data Stored in Relational Databases -- 1 Introduction -- 2 Research Problem -- 3 Related Work -- 4 SQL-Based Declarative Process Mining Framework -- 4.1 Database Creation -- 4.2 SQL-Based Declarative Process Mining -- 5 Benchmarks -- 5.1 Experimental Setting -- 5.2 Results -- 6 Conclusion -- References -- Optimizing the Solution Quality of Metaheuristics Through Process Mining Based on Selected Problems from Operations Research -- 1 Introduction -- 2 Related Work -- 3 Fundamentals -- 3.1 Memetic Algorithms (MA) -- 3.2 Local Process Model Mining -- 4 Solution Method -- 4.1 Operations Research Problems -- 4.2 Encoding and Evaluation -- 4.3 Local Process Model Mining -- 4.4 Memetic Algorithm -- 5 Numerical Experiments -- 5.1 Data and Code -- 5.2 Constraint Programming Formulation -- 5.3 Data Dimensions -- 5.4 Real-World Cobot Assignment and Job Shop Scheduling Problem -- 5.5 Generated Cobot Assignment and Job Shop Scheduling Problem -- 5.6 Cobot Assignment and Flexible Job Shop Scheduling Problem -- 6 Summary and Outlook -- References -- Resource Allocation in Recommender Systems for Global KPI Improvement -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 4 Global Activity-Resource Allocation -- 4.1 Generation of the First Profile -- 4.2 Generation of Additional Profiles -- 4.3 Assign Recommendations -- 5 Evaluation -- 5.1 Introduction to Use Cases -- 5.2 Train-Test Splitting Procedure -- 5.3 Evaluation Metrics | |
| 505 | 8 | |a 5.4 Evaluation Methodology -- 5.5 Results Analysis -- 6 Conclusions -- References -- Zooming in for Clarity: Towards Low-Code Modeling for Activity Data Flow -- 1 Introduction -- 2 Motivating Example and Limitations of BPMN as a Data-Flow Language -- 3 Related Work -- 4 DF-BPMN: DataFlow in Business Process Modeling and Notation -- 4.1 Graphical Process Modeling Using DF-BPMN -- 4.2 DF-BPMN in Action -- 4.3 The Missing Link: Uniting Process and Data for Clarity -- 5 When Processes and Data Meet: Integrating Analysis and Deployment -- 6 Evaluation -- 6.1 Experiment Description -- 6.2 Results -- 7 Discussion and Conclusion -- References -- Management -- Towards a Theory on Process Automation Effects -- 1 Introduction -- 2 Background -- 2.1 Business Processes and Process Automation -- 2.2 General Perspectives on Automation -- 3 Research Method -- 4 Findings -- 4.1 Prerequisites -- 4.2 Interaction -- 4.3 Effects -- 5 Discussion -- 5.1 Process Participant -- 5.2 Process Manager -- 5.3 Software Developers -- 6 Conclusion -- References -- Process Mining and the Transformation of Management Accounting: A Maturity Model for a Holistic Process Performance Measurement System -- 1 Introduction -- 2 Related Work and Research Gaps -- 3 Methodology -- 3.1 Research Design -- 3.2 Data Collection -- 3.3 Data Analysis -- 4 Findings -- 4.1 Process Mining as Enabler of Effective PPM -- 4.2 Organizational and Functional Fragmentation -- 4.3 A Five-Stage Maturity Model for a Holistic and Fully Integrated Process Mining-Supported PPMS -- 5 Conclusion and Future Work -- Appendix -- References -- Conversational Process Modelling: State of the Art, Applications, and Implications in Practice -- 1 Introduction -- 2 Conversational Process Modelling -- 3 State of the Art -- 4 Performance of Current Generation LLMs for Conversational Process Modelling -- 4.1 Test Set Generation | |
| 505 | 8 | |a 4.2 Evaluation | |
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Datensatz im Suchindex
| _version_ | 1820889672260255744 |
|---|---|
| adam_text | |
| any_adam_object | |
| author | Di Francescomarino, Chiara |
| author_facet | Di Francescomarino, Chiara |
| author_role | aut |
| author_sort | Di Francescomarino, Chiara |
| author_variant | f c d fc fcd |
| building | Verbundindex |
| bvnumber | BV050100597 |
| classification_rvk | QP 340 |
| collection | ZDB-30-PQE |
| contents | Intro -- Preface -- Organization -- Contents -- Foundations -- Trusted Compliance Checking on Blockchain with Commitments: A Model-Driven Approach -- 1 Introduction -- 2 Baseline -- 3 Approach -- 3.1 Identifying On-Chain Information -- 3.2 Generating Smart Contract Code -- 3.3 Deploying Smart Contract Code -- 4 Evaluation -- 5 Related Work -- 6 Conclusion -- References -- The Dpex-Framework: Towards Full WFMS Support for Decentralized Process Execution -- 1 Introduction -- 2 Process Execution in a Workflow Management System -- 3 Process Execution in an Interorganizational Context -- 3.1 Message-Based Collaborations -- 3.2 Decentralized Process Execution: Networking Perspective -- 3.3 Decentralized Process Execution: Security Perspective -- 3.4 Blockchain-Based Process Execution -- 4 Architecture for Decentralized Process Execution -- 4.1 Requirements -- 4.2 Architecture -- 5 Implementation and Use Case -- 5.1 dpex-Library -- 5.2 Implementation in a Real-Life Use Case -- 6 Evaluation of the Architecture -- 7 Discussion of Related Work -- 8 Conclusion and Future Work -- References -- A Reference Data Model to Specify Event Logs for Big Data Pipeline Discovery -- 1 Introduction -- 2 Research Methodology -- 3 Background -- 3.1 Process Mining and Event Logs -- 3.2 Big Data Pipelines -- 3.3 Big Data Pipeline Specification Trough DSLs -- 3.4 Use Case -- 4 Reference Model and XES Extension for Event Logs -- 4.1 Reference Data Model -- 4.2 Extending XES -- 5 Demonstration -- 6 Preliminary Evaluation -- 7 Concluding Remarks -- References -- Foundations of Collaborative DECLARE -- 1 Introduction -- 2 A Bird-Eye-View on LTLf and DECLARE -- 2.1 LTLf -- 2.2 DECLARE -- 3 Collaborative DECLARE -- 3.1 Executing a Collaborative Process -- 3.2 Satisfying the Constraints of a Collaborative Process -- 4 Consistency and Enactment of coDECLARE. 4.1 Realizability over Simple Traces -- 4.2 Consistency and Orchestration -- 5 Encoding into LTLf Realizability -- 6 Conclusions -- References -- Declarative Choreographies with Time and Data -- 1 Introduction -- 2 Mixed Timed DCR Choreographies with Data -- 3 Timed DCR Processes with Data and Realizability -- 3.1 Correctness of Realizability -- 3.2 Implementing Synchronous Communication -- 4 Related Work -- 5 Concluding Remarks and Related Work -- References -- Execution Semantics for Process Choreographies with Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Process Choreographies -- 2.2 Interaction Petri Nets -- 3 Motivating Example -- 4 Execution Semantics for Choreographies with Data -- 4.1 Data Exchange Specifications for Choreography Diagrams -- 4.2 Data-Enhanced Interaction Petri Nets -- 4.3 From Choreographies to Data-Enhanced Interaction Petri Nets -- 5 Discussion -- 6 Related Work -- 7 Conclusion -- References -- Large Language Models for Business Process Management: Opportunities and Challenges -- 1 Introduction -- 2 Background -- 2.1 Deep Learning -- 2.2 Large Language Models -- 2.3 Uptake of Large Language Models -- 3 Large Language Models and the BPM Lifecycle -- 3.1 Identification -- 3.2 Discovery -- 3.3 Analysis -- 3.4 Redesign -- 3.5 Implementation -- 3.6 Monitoring -- 4 Research Directions -- 4.1 The Use of Large Language Models in BPM Practice -- 4.2 Usage Guidelines for Researchers and Practitioners -- 4.3 Creation, Release, and Maintenance of Task Variants Specific to BPM -- 4.4 Creation, Release, and Maintenance of Data Sets and Benchmarks -- 4.5 LLM and BPM Artifacts -- 4.6 Development and Release of Large Language Modelss for Business Process Management -- 5 Discussion -- 6 Conclusion -- References -- Engineering -- Predicting Unseen Process Behavior Based on Context Information from Compliance Constraints -- 1 Introduction 2 Problem Statement and Preliminaries -- 3 Next Event Label Prediction Approach -- 3.1 Creating the Prediction Model - Offline Component -- 3.2 Next Event Label Prediction - Online Component -- 4 Evaluation -- 4.1 Data Sets -- 4.2 ATS vs. AATS Without Updates -- 4.3 ATS vs. AATS with Updates -- 4.4 AATS vs. Deep-Learning Model Without Updates -- 4.5 AATS vs. Deep-Learning Model with Updates -- 5 Related Work -- 6 Conclusion -- References -- The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them -- 1 Introduction -- 1.1 Motivation -- 1.2 Example -- 1.3 Approach -- 2 Related Work -- 3 Preliminaries -- 4 Method -- 4.1 Detecting High-Level Behavior Using High-Level Events -- 4.2 Connecting High-Level Events -- 4.3 Case Participation in High-Level Behavior -- 5 Evaluation -- 5.1 The BPI Challenge 2017 Event Log -- 5.2 Experimental Setting and General Statistics -- 5.3 Outcome: Success Rate -- 5.4 Throughput Time -- 6 Conclusion -- References -- Adding the Sustainability Dimension in Process Mining Discovery Algorithms Evaluation -- 1 Introduction -- 2 Background and Related Work -- 2.1 Green BPM -- 2.2 Green Process Mining -- 2.3 Automated Process Discovery Benchmark -- 3 Evaluation -- 3.1 SetUp and Methodology -- 3.2 Benchmark Extension -- 3.3 Results -- 4 Discussion -- 5 Conclusions -- References -- Steady State Estimation for Business Process Simulations -- 1 Introduction -- 2 Related Work -- 3 Running Example -- 4 Preliminaries -- 5 Approach -- 5.1 Event Log Completion -- 5.2 Steady-State Estimation -- 5.3 State Loader -- 6 Evaluation -- 6.1 Real-World Event Log -- 6.2 Running Example Event Log -- 6.3 Discussion -- 7 Conclusion -- References -- Analytics Pipeline for Process Mining on Video Data -- 1 Introduction -- 2 Process Analytics Pipeline -- 2.1 Dataset Preparation -- 2.2 Object Tracking 2.3 Activity Recognition -- 2.4 Event Abstraction -- 2.5 Case Correlation -- 2.6 Process Mining -- 3 Implementation -- 4 Use Case -- 5 Evaluation -- 5.1 Pre-Processing -- 5.2 Event Log Preparation -- 5.3 Result Stability -- 5.4 Result Meaningfulness -- 5.5 Reproducibility and Data Availability -- 6 Related Work -- 7 Conclusion -- References -- An SQL-Based Declarative Process Mining Framework for Analyzing Process Data Stored in Relational Databases -- 1 Introduction -- 2 Research Problem -- 3 Related Work -- 4 SQL-Based Declarative Process Mining Framework -- 4.1 Database Creation -- 4.2 SQL-Based Declarative Process Mining -- 5 Benchmarks -- 5.1 Experimental Setting -- 5.2 Results -- 6 Conclusion -- References -- Optimizing the Solution Quality of Metaheuristics Through Process Mining Based on Selected Problems from Operations Research -- 1 Introduction -- 2 Related Work -- 3 Fundamentals -- 3.1 Memetic Algorithms (MA) -- 3.2 Local Process Model Mining -- 4 Solution Method -- 4.1 Operations Research Problems -- 4.2 Encoding and Evaluation -- 4.3 Local Process Model Mining -- 4.4 Memetic Algorithm -- 5 Numerical Experiments -- 5.1 Data and Code -- 5.2 Constraint Programming Formulation -- 5.3 Data Dimensions -- 5.4 Real-World Cobot Assignment and Job Shop Scheduling Problem -- 5.5 Generated Cobot Assignment and Job Shop Scheduling Problem -- 5.6 Cobot Assignment and Flexible Job Shop Scheduling Problem -- 6 Summary and Outlook -- References -- Resource Allocation in Recommender Systems for Global KPI Improvement -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 4 Global Activity-Resource Allocation -- 4.1 Generation of the First Profile -- 4.2 Generation of Additional Profiles -- 4.3 Assign Recommendations -- 5 Evaluation -- 5.1 Introduction to Use Cases -- 5.2 Train-Test Splitting Procedure -- 5.3 Evaluation Metrics 5.4 Evaluation Methodology -- 5.5 Results Analysis -- 6 Conclusions -- References -- Zooming in for Clarity: Towards Low-Code Modeling for Activity Data Flow -- 1 Introduction -- 2 Motivating Example and Limitations of BPMN as a Data-Flow Language -- 3 Related Work -- 4 DF-BPMN: DataFlow in Business Process Modeling and Notation -- 4.1 Graphical Process Modeling Using DF-BPMN -- 4.2 DF-BPMN in Action -- 4.3 The Missing Link: Uniting Process and Data for Clarity -- 5 When Processes and Data Meet: Integrating Analysis and Deployment -- 6 Evaluation -- 6.1 Experiment Description -- 6.2 Results -- 7 Discussion and Conclusion -- References -- Management -- Towards a Theory on Process Automation Effects -- 1 Introduction -- 2 Background -- 2.1 Business Processes and Process Automation -- 2.2 General Perspectives on Automation -- 3 Research Method -- 4 Findings -- 4.1 Prerequisites -- 4.2 Interaction -- 4.3 Effects -- 5 Discussion -- 5.1 Process Participant -- 5.2 Process Manager -- 5.3 Software Developers -- 6 Conclusion -- References -- Process Mining and the Transformation of Management Accounting: A Maturity Model for a Holistic Process Performance Measurement System -- 1 Introduction -- 2 Related Work and Research Gaps -- 3 Methodology -- 3.1 Research Design -- 3.2 Data Collection -- 3.3 Data Analysis -- 4 Findings -- 4.1 Process Mining as Enabler of Effective PPM -- 4.2 Organizational and Functional Fragmentation -- 4.3 A Five-Stage Maturity Model for a Holistic and Fully Integrated Process Mining-Supported PPMS -- 5 Conclusion and Future Work -- Appendix -- References -- Conversational Process Modelling: State of the Art, Applications, and Implications in Practice -- 1 Introduction -- 2 Conversational Process Modelling -- 3 State of the Art -- 4 Performance of Current Generation LLMs for Conversational Process Modelling -- 4.1 Test Set Generation 4.2 Evaluation |
| ctrlnum | (ZDB-30-PQE)EBC30726191 (ZDB-30-PAD)EBC30726191 (ZDB-89-EBL)EBL30726191 (OCoLC)1396226291 (DE-599)BVBBV050100597 |
| dewey-full | 658.05 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.05 |
| dewey-search | 658.05 |
| dewey-sort | 3658.05 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| edition | 1st ed |
| format | Electronic eBook |
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Satisfying the Constraints of a Collaborative Process -- 4 Consistency and Enactment of coDECLARE.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4.1 Realizability over Simple Traces -- 4.2 Consistency and Orchestration -- 5 Encoding into LTLf Realizability -- 6 Conclusions -- References -- Declarative Choreographies with Time and Data -- 1 Introduction -- 2 Mixed Timed DCR Choreographies with Data -- 3 Timed DCR Processes with Data and Realizability -- 3.1 Correctness of Realizability -- 3.2 Implementing Synchronous Communication -- 4 Related Work -- 5 Concluding Remarks and Related Work -- References -- Execution Semantics for Process Choreographies with Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Process Choreographies -- 2.2 Interaction Petri Nets -- 3 Motivating Example -- 4 Execution Semantics for Choreographies with Data -- 4.1 Data Exchange Specifications for Choreography Diagrams -- 4.2 Data-Enhanced Interaction Petri Nets -- 4.3 From Choreographies to Data-Enhanced Interaction Petri Nets -- 5 Discussion -- 6 Related Work -- 7 Conclusion -- References -- Large Language Models for Business Process Management: Opportunities and Challenges -- 1 Introduction -- 2 Background -- 2.1 Deep Learning -- 2.2 Large Language Models -- 2.3 Uptake of Large Language Models -- 3 Large Language Models and the BPM Lifecycle -- 3.1 Identification -- 3.2 Discovery -- 3.3 Analysis -- 3.4 Redesign -- 3.5 Implementation -- 3.6 Monitoring -- 4 Research Directions -- 4.1 The Use of Large Language Models in BPM Practice -- 4.2 Usage Guidelines for Researchers and Practitioners -- 4.3 Creation, Release, and Maintenance of Task Variants Specific to BPM -- 4.4 Creation, Release, and Maintenance of Data Sets and Benchmarks -- 4.5 LLM and BPM Artifacts -- 4.6 Development and Release of Large Language Modelss for Business Process Management -- 5 Discussion -- 6 Conclusion -- References -- Engineering -- Predicting Unseen Process Behavior Based on Context Information from Compliance Constraints -- 1 Introduction</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">2 Problem Statement and Preliminaries -- 3 Next Event Label Prediction Approach -- 3.1 Creating the Prediction Model - Offline Component -- 3.2 Next Event Label Prediction - Online Component -- 4 Evaluation -- 4.1 Data Sets -- 4.2 ATS vs. AATS Without Updates -- 4.3 ATS vs. AATS with Updates -- 4.4 AATS vs. Deep-Learning Model Without Updates -- 4.5 AATS vs. Deep-Learning Model with Updates -- 5 Related Work -- 6 Conclusion -- References -- The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them -- 1 Introduction -- 1.1 Motivation -- 1.2 Example -- 1.3 Approach -- 2 Related Work -- 3 Preliminaries -- 4 Method -- 4.1 Detecting High-Level Behavior Using High-Level Events -- 4.2 Connecting High-Level Events -- 4.3 Case Participation in High-Level Behavior -- 5 Evaluation -- 5.1 The BPI Challenge 2017 Event Log -- 5.2 Experimental Setting and General Statistics -- 5.3 Outcome: Success Rate -- 5.4 Throughput Time -- 6 Conclusion -- References -- Adding the Sustainability Dimension in Process Mining Discovery Algorithms Evaluation -- 1 Introduction -- 2 Background and Related Work -- 2.1 Green BPM -- 2.2 Green Process Mining -- 2.3 Automated Process Discovery Benchmark -- 3 Evaluation -- 3.1 SetUp and Methodology -- 3.2 Benchmark Extension -- 3.3 Results -- 4 Discussion -- 5 Conclusions -- References -- Steady State Estimation for Business Process Simulations -- 1 Introduction -- 2 Related Work -- 3 Running Example -- 4 Preliminaries -- 5 Approach -- 5.1 Event Log Completion -- 5.2 Steady-State Estimation -- 5.3 State Loader -- 6 Evaluation -- 6.1 Real-World Event Log -- 6.2 Running Example Event Log -- 6.3 Discussion -- 7 Conclusion -- References -- Analytics Pipeline for Process Mining on Video Data -- 1 Introduction -- 2 Process Analytics Pipeline -- 2.1 Dataset Preparation -- 2.2 Object Tracking</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">2.3 Activity Recognition -- 2.4 Event Abstraction -- 2.5 Case Correlation -- 2.6 Process Mining -- 3 Implementation -- 4 Use Case -- 5 Evaluation -- 5.1 Pre-Processing -- 5.2 Event Log Preparation -- 5.3 Result Stability -- 5.4 Result Meaningfulness -- 5.5 Reproducibility and Data Availability -- 6 Related Work -- 7 Conclusion -- References -- An SQL-Based Declarative Process Mining Framework for Analyzing Process Data Stored in Relational Databases -- 1 Introduction -- 2 Research Problem -- 3 Related Work -- 4 SQL-Based Declarative Process Mining Framework -- 4.1 Database Creation -- 4.2 SQL-Based Declarative Process Mining -- 5 Benchmarks -- 5.1 Experimental Setting -- 5.2 Results -- 6 Conclusion -- References -- Optimizing the Solution Quality of Metaheuristics Through Process Mining Based on Selected Problems from Operations Research -- 1 Introduction -- 2 Related Work -- 3 Fundamentals -- 3.1 Memetic Algorithms (MA) -- 3.2 Local Process Model Mining -- 4 Solution Method -- 4.1 Operations Research Problems -- 4.2 Encoding and Evaluation -- 4.3 Local Process Model Mining -- 4.4 Memetic Algorithm -- 5 Numerical Experiments -- 5.1 Data and Code -- 5.2 Constraint Programming Formulation -- 5.3 Data Dimensions -- 5.4 Real-World Cobot Assignment and Job Shop Scheduling Problem -- 5.5 Generated Cobot Assignment and Job Shop Scheduling Problem -- 5.6 Cobot Assignment and Flexible Job Shop Scheduling Problem -- 6 Summary and Outlook -- References -- Resource Allocation in Recommender Systems for Global KPI Improvement -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 4 Global Activity-Resource Allocation -- 4.1 Generation of the First Profile -- 4.2 Generation of Additional Profiles -- 4.3 Assign Recommendations -- 5 Evaluation -- 5.1 Introduction to Use Cases -- 5.2 Train-Test Splitting Procedure -- 5.3 Evaluation Metrics</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">5.4 Evaluation Methodology -- 5.5 Results Analysis -- 6 Conclusions -- References -- Zooming in for Clarity: Towards Low-Code Modeling for Activity Data Flow -- 1 Introduction -- 2 Motivating Example and Limitations of BPMN as a Data-Flow Language -- 3 Related Work -- 4 DF-BPMN: DataFlow in Business Process Modeling and Notation -- 4.1 Graphical Process Modeling Using DF-BPMN -- 4.2 DF-BPMN in Action -- 4.3 The Missing Link: Uniting Process and Data for Clarity -- 5 When Processes and Data Meet: Integrating Analysis and Deployment -- 6 Evaluation -- 6.1 Experiment Description -- 6.2 Results -- 7 Discussion and Conclusion -- References -- Management -- Towards a Theory on Process Automation Effects -- 1 Introduction -- 2 Background -- 2.1 Business Processes and Process Automation -- 2.2 General Perspectives on Automation -- 3 Research Method -- 4 Findings -- 4.1 Prerequisites -- 4.2 Interaction -- 4.3 Effects -- 5 Discussion -- 5.1 Process Participant -- 5.2 Process Manager -- 5.3 Software Developers -- 6 Conclusion -- References -- Process Mining and the Transformation of Management Accounting: A Maturity Model for a Holistic Process Performance Measurement System -- 1 Introduction -- 2 Related Work and Research Gaps -- 3 Methodology -- 3.1 Research Design -- 3.2 Data Collection -- 3.3 Data Analysis -- 4 Findings -- 4.1 Process Mining as Enabler of Effective PPM -- 4.2 Organizational and Functional Fragmentation -- 4.3 A Five-Stage Maturity Model for a Holistic and Fully Integrated Process Mining-Supported PPMS -- 5 Conclusion and Future Work -- Appendix -- References -- Conversational Process Modelling: State of the Art, Applications, and Implications in Practice -- 1 Introduction -- 2 Conversational Process Modelling -- 3 State of the Art -- 4 Performance of Current Generation LLMs for Conversational Process Modelling -- 4.1 Test Set Generation</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4.2 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| genre | (DE-588)1071861417 Konferenzschrift 2023 Utrecht gnd-content |
| genre_facet | Konferenzschrift 2023 Utrecht |
| id | DE-604.BV050100597 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-10T19:01:53Z |
| institution | BVB |
| isbn | 9783031416231 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035437759 |
| oclc_num | 1396226291 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (423 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Springer |
| record_format | marc |
| series2 | Lecture Notes in Business Information Processing Series |
| spelling | Di Francescomarino, Chiara Verfasser aut Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings 1st ed Cham Springer 2023 ©2023 1 Online-Ressource (423 Seiten) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Business Information Processing Series v.490 Description based on publisher supplied metadata and other sources Intro -- Preface -- Organization -- Contents -- Foundations -- Trusted Compliance Checking on Blockchain with Commitments: A Model-Driven Approach -- 1 Introduction -- 2 Baseline -- 3 Approach -- 3.1 Identifying On-Chain Information -- 3.2 Generating Smart Contract Code -- 3.3 Deploying Smart Contract Code -- 4 Evaluation -- 5 Related Work -- 6 Conclusion -- References -- The Dpex-Framework: Towards Full WFMS Support for Decentralized Process Execution -- 1 Introduction -- 2 Process Execution in a Workflow Management System -- 3 Process Execution in an Interorganizational Context -- 3.1 Message-Based Collaborations -- 3.2 Decentralized Process Execution: Networking Perspective -- 3.3 Decentralized Process Execution: Security Perspective -- 3.4 Blockchain-Based Process Execution -- 4 Architecture for Decentralized Process Execution -- 4.1 Requirements -- 4.2 Architecture -- 5 Implementation and Use Case -- 5.1 dpex-Library -- 5.2 Implementation in a Real-Life Use Case -- 6 Evaluation of the Architecture -- 7 Discussion of Related Work -- 8 Conclusion and Future Work -- References -- A Reference Data Model to Specify Event Logs for Big Data Pipeline Discovery -- 1 Introduction -- 2 Research Methodology -- 3 Background -- 3.1 Process Mining and Event Logs -- 3.2 Big Data Pipelines -- 3.3 Big Data Pipeline Specification Trough DSLs -- 3.4 Use Case -- 4 Reference Model and XES Extension for Event Logs -- 4.1 Reference Data Model -- 4.2 Extending XES -- 5 Demonstration -- 6 Preliminary Evaluation -- 7 Concluding Remarks -- References -- Foundations of Collaborative DECLARE -- 1 Introduction -- 2 A Bird-Eye-View on LTLf and DECLARE -- 2.1 LTLf -- 2.2 DECLARE -- 3 Collaborative DECLARE -- 3.1 Executing a Collaborative Process -- 3.2 Satisfying the Constraints of a Collaborative Process -- 4 Consistency and Enactment of coDECLARE. 4.1 Realizability over Simple Traces -- 4.2 Consistency and Orchestration -- 5 Encoding into LTLf Realizability -- 6 Conclusions -- References -- Declarative Choreographies with Time and Data -- 1 Introduction -- 2 Mixed Timed DCR Choreographies with Data -- 3 Timed DCR Processes with Data and Realizability -- 3.1 Correctness of Realizability -- 3.2 Implementing Synchronous Communication -- 4 Related Work -- 5 Concluding Remarks and Related Work -- References -- Execution Semantics for Process Choreographies with Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Process Choreographies -- 2.2 Interaction Petri Nets -- 3 Motivating Example -- 4 Execution Semantics for Choreographies with Data -- 4.1 Data Exchange Specifications for Choreography Diagrams -- 4.2 Data-Enhanced Interaction Petri Nets -- 4.3 From Choreographies to Data-Enhanced Interaction Petri Nets -- 5 Discussion -- 6 Related Work -- 7 Conclusion -- References -- Large Language Models for Business Process Management: Opportunities and Challenges -- 1 Introduction -- 2 Background -- 2.1 Deep Learning -- 2.2 Large Language Models -- 2.3 Uptake of Large Language Models -- 3 Large Language Models and the BPM Lifecycle -- 3.1 Identification -- 3.2 Discovery -- 3.3 Analysis -- 3.4 Redesign -- 3.5 Implementation -- 3.6 Monitoring -- 4 Research Directions -- 4.1 The Use of Large Language Models in BPM Practice -- 4.2 Usage Guidelines for Researchers and Practitioners -- 4.3 Creation, Release, and Maintenance of Task Variants Specific to BPM -- 4.4 Creation, Release, and Maintenance of Data Sets and Benchmarks -- 4.5 LLM and BPM Artifacts -- 4.6 Development and Release of Large Language Modelss for Business Process Management -- 5 Discussion -- 6 Conclusion -- References -- Engineering -- Predicting Unseen Process Behavior Based on Context Information from Compliance Constraints -- 1 Introduction 2 Problem Statement and Preliminaries -- 3 Next Event Label Prediction Approach -- 3.1 Creating the Prediction Model - Offline Component -- 3.2 Next Event Label Prediction - Online Component -- 4 Evaluation -- 4.1 Data Sets -- 4.2 ATS vs. AATS Without Updates -- 4.3 ATS vs. AATS with Updates -- 4.4 AATS vs. Deep-Learning Model Without Updates -- 4.5 AATS vs. Deep-Learning Model with Updates -- 5 Related Work -- 6 Conclusion -- References -- The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them -- 1 Introduction -- 1.1 Motivation -- 1.2 Example -- 1.3 Approach -- 2 Related Work -- 3 Preliminaries -- 4 Method -- 4.1 Detecting High-Level Behavior Using High-Level Events -- 4.2 Connecting High-Level Events -- 4.3 Case Participation in High-Level Behavior -- 5 Evaluation -- 5.1 The BPI Challenge 2017 Event Log -- 5.2 Experimental Setting and General Statistics -- 5.3 Outcome: Success Rate -- 5.4 Throughput Time -- 6 Conclusion -- References -- Adding the Sustainability Dimension in Process Mining Discovery Algorithms Evaluation -- 1 Introduction -- 2 Background and Related Work -- 2.1 Green BPM -- 2.2 Green Process Mining -- 2.3 Automated Process Discovery Benchmark -- 3 Evaluation -- 3.1 SetUp and Methodology -- 3.2 Benchmark Extension -- 3.3 Results -- 4 Discussion -- 5 Conclusions -- References -- Steady State Estimation for Business Process Simulations -- 1 Introduction -- 2 Related Work -- 3 Running Example -- 4 Preliminaries -- 5 Approach -- 5.1 Event Log Completion -- 5.2 Steady-State Estimation -- 5.3 State Loader -- 6 Evaluation -- 6.1 Real-World Event Log -- 6.2 Running Example Event Log -- 6.3 Discussion -- 7 Conclusion -- References -- Analytics Pipeline for Process Mining on Video Data -- 1 Introduction -- 2 Process Analytics Pipeline -- 2.1 Dataset Preparation -- 2.2 Object Tracking 2.3 Activity Recognition -- 2.4 Event Abstraction -- 2.5 Case Correlation -- 2.6 Process Mining -- 3 Implementation -- 4 Use Case -- 5 Evaluation -- 5.1 Pre-Processing -- 5.2 Event Log Preparation -- 5.3 Result Stability -- 5.4 Result Meaningfulness -- 5.5 Reproducibility and Data Availability -- 6 Related Work -- 7 Conclusion -- References -- An SQL-Based Declarative Process Mining Framework for Analyzing Process Data Stored in Relational Databases -- 1 Introduction -- 2 Research Problem -- 3 Related Work -- 4 SQL-Based Declarative Process Mining Framework -- 4.1 Database Creation -- 4.2 SQL-Based Declarative Process Mining -- 5 Benchmarks -- 5.1 Experimental Setting -- 5.2 Results -- 6 Conclusion -- References -- Optimizing the Solution Quality of Metaheuristics Through Process Mining Based on Selected Problems from Operations Research -- 1 Introduction -- 2 Related Work -- 3 Fundamentals -- 3.1 Memetic Algorithms (MA) -- 3.2 Local Process Model Mining -- 4 Solution Method -- 4.1 Operations Research Problems -- 4.2 Encoding and Evaluation -- 4.3 Local Process Model Mining -- 4.4 Memetic Algorithm -- 5 Numerical Experiments -- 5.1 Data and Code -- 5.2 Constraint Programming Formulation -- 5.3 Data Dimensions -- 5.4 Real-World Cobot Assignment and Job Shop Scheduling Problem -- 5.5 Generated Cobot Assignment and Job Shop Scheduling Problem -- 5.6 Cobot Assignment and Flexible Job Shop Scheduling Problem -- 6 Summary and Outlook -- References -- Resource Allocation in Recommender Systems for Global KPI Improvement -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 4 Global Activity-Resource Allocation -- 4.1 Generation of the First Profile -- 4.2 Generation of Additional Profiles -- 4.3 Assign Recommendations -- 5 Evaluation -- 5.1 Introduction to Use Cases -- 5.2 Train-Test Splitting Procedure -- 5.3 Evaluation Metrics 5.4 Evaluation Methodology -- 5.5 Results Analysis -- 6 Conclusions -- References -- Zooming in for Clarity: Towards Low-Code Modeling for Activity Data Flow -- 1 Introduction -- 2 Motivating Example and Limitations of BPMN as a Data-Flow Language -- 3 Related Work -- 4 DF-BPMN: DataFlow in Business Process Modeling and Notation -- 4.1 Graphical Process Modeling Using DF-BPMN -- 4.2 DF-BPMN in Action -- 4.3 The Missing Link: Uniting Process and Data for Clarity -- 5 When Processes and Data Meet: Integrating Analysis and Deployment -- 6 Evaluation -- 6.1 Experiment Description -- 6.2 Results -- 7 Discussion and Conclusion -- References -- Management -- Towards a Theory on Process Automation Effects -- 1 Introduction -- 2 Background -- 2.1 Business Processes and Process Automation -- 2.2 General Perspectives on Automation -- 3 Research Method -- 4 Findings -- 4.1 Prerequisites -- 4.2 Interaction -- 4.3 Effects -- 5 Discussion -- 5.1 Process Participant -- 5.2 Process Manager -- 5.3 Software Developers -- 6 Conclusion -- References -- Process Mining and the Transformation of Management Accounting: A Maturity Model for a Holistic Process Performance Measurement System -- 1 Introduction -- 2 Related Work and Research Gaps -- 3 Methodology -- 3.1 Research Design -- 3.2 Data Collection -- 3.3 Data Analysis -- 4 Findings -- 4.1 Process Mining as Enabler of Effective PPM -- 4.2 Organizational and Functional Fragmentation -- 4.3 A Five-Stage Maturity Model for a Holistic and Fully Integrated Process Mining-Supported PPMS -- 5 Conclusion and Future Work -- Appendix -- References -- Conversational Process Modelling: State of the Art, Applications, and Implications in Practice -- 1 Introduction -- 2 Conversational Process Modelling -- 3 State of the Art -- 4 Performance of Current Generation LLMs for Conversational Process Modelling -- 4.1 Test Set Generation 4.2 Evaluation Prozessmanagement (DE-588)4353072-2 gnd rswk-swf (DE-588)1071861417 Konferenzschrift 2023 Utrecht gnd-content Prozessmanagement (DE-588)4353072-2 s DE-604 Burattin, Andrea Sonstige oth Janiesch, Christian Sonstige oth Sadiq, Shazia Sonstige oth Erscheint auch als Druck-Ausgabe Di Francescomarino, Chiara Business Process Management Forum Cham : Springer,c2023 9783031416224 |
| spellingShingle | Di Francescomarino, Chiara Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings Intro -- Preface -- Organization -- Contents -- Foundations -- Trusted Compliance Checking on Blockchain with Commitments: A Model-Driven Approach -- 1 Introduction -- 2 Baseline -- 3 Approach -- 3.1 Identifying On-Chain Information -- 3.2 Generating Smart Contract Code -- 3.3 Deploying Smart Contract Code -- 4 Evaluation -- 5 Related Work -- 6 Conclusion -- References -- The Dpex-Framework: Towards Full WFMS Support for Decentralized Process Execution -- 1 Introduction -- 2 Process Execution in a Workflow Management System -- 3 Process Execution in an Interorganizational Context -- 3.1 Message-Based Collaborations -- 3.2 Decentralized Process Execution: Networking Perspective -- 3.3 Decentralized Process Execution: Security Perspective -- 3.4 Blockchain-Based Process Execution -- 4 Architecture for Decentralized Process Execution -- 4.1 Requirements -- 4.2 Architecture -- 5 Implementation and Use Case -- 5.1 dpex-Library -- 5.2 Implementation in a Real-Life Use Case -- 6 Evaluation of the Architecture -- 7 Discussion of Related Work -- 8 Conclusion and Future Work -- References -- A Reference Data Model to Specify Event Logs for Big Data Pipeline Discovery -- 1 Introduction -- 2 Research Methodology -- 3 Background -- 3.1 Process Mining and Event Logs -- 3.2 Big Data Pipelines -- 3.3 Big Data Pipeline Specification Trough DSLs -- 3.4 Use Case -- 4 Reference Model and XES Extension for Event Logs -- 4.1 Reference Data Model -- 4.2 Extending XES -- 5 Demonstration -- 6 Preliminary Evaluation -- 7 Concluding Remarks -- References -- Foundations of Collaborative DECLARE -- 1 Introduction -- 2 A Bird-Eye-View on LTLf and DECLARE -- 2.1 LTLf -- 2.2 DECLARE -- 3 Collaborative DECLARE -- 3.1 Executing a Collaborative Process -- 3.2 Satisfying the Constraints of a Collaborative Process -- 4 Consistency and Enactment of coDECLARE. 4.1 Realizability over Simple Traces -- 4.2 Consistency and Orchestration -- 5 Encoding into LTLf Realizability -- 6 Conclusions -- References -- Declarative Choreographies with Time and Data -- 1 Introduction -- 2 Mixed Timed DCR Choreographies with Data -- 3 Timed DCR Processes with Data and Realizability -- 3.1 Correctness of Realizability -- 3.2 Implementing Synchronous Communication -- 4 Related Work -- 5 Concluding Remarks and Related Work -- References -- Execution Semantics for Process Choreographies with Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Process Choreographies -- 2.2 Interaction Petri Nets -- 3 Motivating Example -- 4 Execution Semantics for Choreographies with Data -- 4.1 Data Exchange Specifications for Choreography Diagrams -- 4.2 Data-Enhanced Interaction Petri Nets -- 4.3 From Choreographies to Data-Enhanced Interaction Petri Nets -- 5 Discussion -- 6 Related Work -- 7 Conclusion -- References -- Large Language Models for Business Process Management: Opportunities and Challenges -- 1 Introduction -- 2 Background -- 2.1 Deep Learning -- 2.2 Large Language Models -- 2.3 Uptake of Large Language Models -- 3 Large Language Models and the BPM Lifecycle -- 3.1 Identification -- 3.2 Discovery -- 3.3 Analysis -- 3.4 Redesign -- 3.5 Implementation -- 3.6 Monitoring -- 4 Research Directions -- 4.1 The Use of Large Language Models in BPM Practice -- 4.2 Usage Guidelines for Researchers and Practitioners -- 4.3 Creation, Release, and Maintenance of Task Variants Specific to BPM -- 4.4 Creation, Release, and Maintenance of Data Sets and Benchmarks -- 4.5 LLM and BPM Artifacts -- 4.6 Development and Release of Large Language Modelss for Business Process Management -- 5 Discussion -- 6 Conclusion -- References -- Engineering -- Predicting Unseen Process Behavior Based on Context Information from Compliance Constraints -- 1 Introduction 2 Problem Statement and Preliminaries -- 3 Next Event Label Prediction Approach -- 3.1 Creating the Prediction Model - Offline Component -- 3.2 Next Event Label Prediction - Online Component -- 4 Evaluation -- 4.1 Data Sets -- 4.2 ATS vs. AATS Without Updates -- 4.3 ATS vs. AATS with Updates -- 4.4 AATS vs. Deep-Learning Model Without Updates -- 4.5 AATS vs. Deep-Learning Model with Updates -- 5 Related Work -- 6 Conclusion -- References -- The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them -- 1 Introduction -- 1.1 Motivation -- 1.2 Example -- 1.3 Approach -- 2 Related Work -- 3 Preliminaries -- 4 Method -- 4.1 Detecting High-Level Behavior Using High-Level Events -- 4.2 Connecting High-Level Events -- 4.3 Case Participation in High-Level Behavior -- 5 Evaluation -- 5.1 The BPI Challenge 2017 Event Log -- 5.2 Experimental Setting and General Statistics -- 5.3 Outcome: Success Rate -- 5.4 Throughput Time -- 6 Conclusion -- References -- Adding the Sustainability Dimension in Process Mining Discovery Algorithms Evaluation -- 1 Introduction -- 2 Background and Related Work -- 2.1 Green BPM -- 2.2 Green Process Mining -- 2.3 Automated Process Discovery Benchmark -- 3 Evaluation -- 3.1 SetUp and Methodology -- 3.2 Benchmark Extension -- 3.3 Results -- 4 Discussion -- 5 Conclusions -- References -- Steady State Estimation for Business Process Simulations -- 1 Introduction -- 2 Related Work -- 3 Running Example -- 4 Preliminaries -- 5 Approach -- 5.1 Event Log Completion -- 5.2 Steady-State Estimation -- 5.3 State Loader -- 6 Evaluation -- 6.1 Real-World Event Log -- 6.2 Running Example Event Log -- 6.3 Discussion -- 7 Conclusion -- References -- Analytics Pipeline for Process Mining on Video Data -- 1 Introduction -- 2 Process Analytics Pipeline -- 2.1 Dataset Preparation -- 2.2 Object Tracking 2.3 Activity Recognition -- 2.4 Event Abstraction -- 2.5 Case Correlation -- 2.6 Process Mining -- 3 Implementation -- 4 Use Case -- 5 Evaluation -- 5.1 Pre-Processing -- 5.2 Event Log Preparation -- 5.3 Result Stability -- 5.4 Result Meaningfulness -- 5.5 Reproducibility and Data Availability -- 6 Related Work -- 7 Conclusion -- References -- An SQL-Based Declarative Process Mining Framework for Analyzing Process Data Stored in Relational Databases -- 1 Introduction -- 2 Research Problem -- 3 Related Work -- 4 SQL-Based Declarative Process Mining Framework -- 4.1 Database Creation -- 4.2 SQL-Based Declarative Process Mining -- 5 Benchmarks -- 5.1 Experimental Setting -- 5.2 Results -- 6 Conclusion -- References -- Optimizing the Solution Quality of Metaheuristics Through Process Mining Based on Selected Problems from Operations Research -- 1 Introduction -- 2 Related Work -- 3 Fundamentals -- 3.1 Memetic Algorithms (MA) -- 3.2 Local Process Model Mining -- 4 Solution Method -- 4.1 Operations Research Problems -- 4.2 Encoding and Evaluation -- 4.3 Local Process Model Mining -- 4.4 Memetic Algorithm -- 5 Numerical Experiments -- 5.1 Data and Code -- 5.2 Constraint Programming Formulation -- 5.3 Data Dimensions -- 5.4 Real-World Cobot Assignment and Job Shop Scheduling Problem -- 5.5 Generated Cobot Assignment and Job Shop Scheduling Problem -- 5.6 Cobot Assignment and Flexible Job Shop Scheduling Problem -- 6 Summary and Outlook -- References -- Resource Allocation in Recommender Systems for Global KPI Improvement -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 4 Global Activity-Resource Allocation -- 4.1 Generation of the First Profile -- 4.2 Generation of Additional Profiles -- 4.3 Assign Recommendations -- 5 Evaluation -- 5.1 Introduction to Use Cases -- 5.2 Train-Test Splitting Procedure -- 5.3 Evaluation Metrics 5.4 Evaluation Methodology -- 5.5 Results Analysis -- 6 Conclusions -- References -- Zooming in for Clarity: Towards Low-Code Modeling for Activity Data Flow -- 1 Introduction -- 2 Motivating Example and Limitations of BPMN as a Data-Flow Language -- 3 Related Work -- 4 DF-BPMN: DataFlow in Business Process Modeling and Notation -- 4.1 Graphical Process Modeling Using DF-BPMN -- 4.2 DF-BPMN in Action -- 4.3 The Missing Link: Uniting Process and Data for Clarity -- 5 When Processes and Data Meet: Integrating Analysis and Deployment -- 6 Evaluation -- 6.1 Experiment Description -- 6.2 Results -- 7 Discussion and Conclusion -- References -- Management -- Towards a Theory on Process Automation Effects -- 1 Introduction -- 2 Background -- 2.1 Business Processes and Process Automation -- 2.2 General Perspectives on Automation -- 3 Research Method -- 4 Findings -- 4.1 Prerequisites -- 4.2 Interaction -- 4.3 Effects -- 5 Discussion -- 5.1 Process Participant -- 5.2 Process Manager -- 5.3 Software Developers -- 6 Conclusion -- References -- Process Mining and the Transformation of Management Accounting: A Maturity Model for a Holistic Process Performance Measurement System -- 1 Introduction -- 2 Related Work and Research Gaps -- 3 Methodology -- 3.1 Research Design -- 3.2 Data Collection -- 3.3 Data Analysis -- 4 Findings -- 4.1 Process Mining as Enabler of Effective PPM -- 4.2 Organizational and Functional Fragmentation -- 4.3 A Five-Stage Maturity Model for a Holistic and Fully Integrated Process Mining-Supported PPMS -- 5 Conclusion and Future Work -- Appendix -- References -- Conversational Process Modelling: State of the Art, Applications, and Implications in Practice -- 1 Introduction -- 2 Conversational Process Modelling -- 3 State of the Art -- 4 Performance of Current Generation LLMs for Conversational Process Modelling -- 4.1 Test Set Generation 4.2 Evaluation Prozessmanagement (DE-588)4353072-2 gnd |
| subject_GND | (DE-588)4353072-2 (DE-588)1071861417 |
| title | Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings |
| title_auth | Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings |
| title_exact_search | Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings |
| title_full | Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings |
| title_fullStr | Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings |
| title_full_unstemmed | Business Process Management Forum BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings |
| title_short | Business Process Management Forum |
| title_sort | business process management forum bpm 2023 forum utrecht the netherlands september 11 15 2023 proceedings |
| title_sub | BPM 2023 Forum, Utrecht, the Netherlands, September 11-15, 2023, Proceedings |
| topic | Prozessmanagement (DE-588)4353072-2 gnd |
| topic_facet | Prozessmanagement Konferenzschrift 2023 Utrecht |
| work_keys_str_mv | AT difrancescomarinochiara businessprocessmanagementforumbpm2023forumutrechtthenetherlandsseptember11152023proceedings AT burattinandrea businessprocessmanagementforumbpm2023forumutrechtthenetherlandsseptember11152023proceedings AT janieschchristian businessprocessmanagementforumbpm2023forumutrechtthenetherlandsseptember11152023proceedings AT sadiqshazia businessprocessmanagementforumbpm2023forumutrechtthenetherlandsseptember11152023proceedings |