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Business Process Management: Blockchain, Robotic Process Automation and Educators Forum [[electronic resource] ] : BPM 2023 Blockchain, RPA and Educators Forum, Utrecht, The Netherlands, September 11–15, 2023, Proceedings / / edited by Julius Köpke, Orlenys López-Pintado, Ralf Plattfaut, Jana-Rebecca Rehse, Katarzyna Gdowska, Fernanda Gonzalez-Lopez, Jorge Munoz-Gama, Koen Smit, Jan Martijn E. M. van der Werf
| Business Process Management: Blockchain, Robotic Process Automation and Educators Forum [[electronic resource] ] : BPM 2023 Blockchain, RPA and Educators Forum, Utrecht, The Netherlands, September 11–15, 2023, Proceedings / / edited by Julius Köpke, Orlenys López-Pintado, Ralf Plattfaut, Jana-Rebecca Rehse, Katarzyna Gdowska, Fernanda Gonzalez-Lopez, Jorge Munoz-Gama, Koen Smit, Jan Martijn E. M. van der Werf |
| Autore | Köpke Julius |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (274 pages) |
| Disciplina | 005.3 |
| Altri autori (Persone) |
López-PintadoOrlenys
PlattfautRalf RehseJana-Rebecca GdowskaKatarzyna Gonzalez-LopezFernanda Munoz-GamaJorge SmitKoen van der WerfJan Martijn E. M |
| Collana | Lecture Notes in Business Information Processing |
| Soggetto topico |
Application software
Business information services Data protection Control engineering Robotics Automation Education - Data processing Industrial engineering Computer and Information Systems Applications IT in Business Data and Information Security Control, Robotics, Automation Computers and Education Industrial Automation |
| ISBN | 3-031-43433-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Blockchain Forum -- RPA Forum -- Educators Forum. |
| Record Nr. | UNISA-996550561003316 |
Köpke Julius
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Business Process Management: Blockchain, Robotic Process Automation and Educators Forum [[electronic resource] ] : BPM 2023 Blockchain, RPA and Educators Forum, Utrecht, The Netherlands, September 11–15, 2023, Proceedings / / edited by Julius Köpke, Orlenys López-Pintado, Ralf Plattfaut, Jana-Rebecca Rehse, Katarzyna Gdowska, Fernanda Gonzalez-Lopez, Jorge Munoz-Gama, Koen Smit, Jan Martijn E. M. van der Werf
| Business Process Management: Blockchain, Robotic Process Automation and Educators Forum [[electronic resource] ] : BPM 2023 Blockchain, RPA and Educators Forum, Utrecht, The Netherlands, September 11–15, 2023, Proceedings / / edited by Julius Köpke, Orlenys López-Pintado, Ralf Plattfaut, Jana-Rebecca Rehse, Katarzyna Gdowska, Fernanda Gonzalez-Lopez, Jorge Munoz-Gama, Koen Smit, Jan Martijn E. M. van der Werf |
| Autore | Köpke Julius |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (274 pages) |
| Disciplina | 005.3 |
| Altri autori (Persone) |
López-PintadoOrlenys
PlattfautRalf RehseJana-Rebecca GdowskaKatarzyna Gonzalez-LopezFernanda Munoz-GamaJorge SmitKoen van der WerfJan Martijn E. M |
| Collana | Lecture Notes in Business Information Processing |
| Soggetto topico |
Application software
Business information services Data protection Control engineering Robotics Automation Education - Data processing Industrial engineering Computer and Information Systems Applications IT in Business Data and Information Security Control, Robotics, Automation Computers and Education Industrial Automation |
| ISBN | 3-031-43433-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Blockchain Forum -- RPA Forum -- Educators Forum. |
| Record Nr. | UNINA-9910743684503321 |
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Köpke Julius
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||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Explainable Artificial Intelligence and Process Mining Applications for Healthcare : Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings
| Explainable Artificial Intelligence and Process Mining Applications for Healthcare : Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings |
| Autore | Juarez Jose M |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (140 pages) |
| Altri autori (Persone) |
Fernandez-LlatasCarlos
BielzaConcha JohnsonOwen KocbekPrimoz LarrañagaPedro MartinNiels Munoz-GamaJorge StiglicGregor SepulvedaMarcos |
| Collana | Communications in Computer and Information Science Series |
| ISBN | 3-031-54303-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- International Workshop on Explainable Artificial Intelligence in Healthcare -- Unlocking the Power of Explainability in Ranking Systems: A Visual Analytics Approach with XAI Techniques -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 XAI -- 3.2 Interactive Visualization -- 4 Case Study: Explaining Triaging Patients to Be Admitted to ICU -- 5 Discussion -- 6 Conclusion -- References -- Explainable Artificial Intelligence in Response to the Failures of Musculoskeletal Disorder Rehabilitation -- 1 Introduction -- 2 Background and Context of This Work -- 3 Complexity of the Generation of Self-recovery Exercises -- 3.1 Defining the Rules -- 3.2 Application of the Consensus Rules -- 4 General Structure of Recov'Up -- 5 Explicability -- 6 Data Extension and Perspectives -- References -- An Explainable AI Framework for Treatment Failure Model for Oncology Patients -- 1 Introduction -- 2 Scope of Work -- 2.1 Approaches to Explainability -- 3 Methodology -- 3.1 Treatment Failure Explanations -- 3.2 Model Level Explanations -- 3.3 Challenges and Limitations -- 4 Results and Discussion -- 4.1 Dataset Insights -- 4.2 Treatment Failure Explanations -- 4.3 Counterfactual -- 4.4 Model Level Explanations -- 5 Conclusion and Future Work -- References -- Feature Selection in Bipolar Disorder Episode Classification Using Cost-Constrained Methods -- 1 Introduction -- 2 Methodology -- 2.1 Data Preprocessing -- 2.2 Algorithm -- 3 Preliminary Results -- 4 Conclusions and Future Plans -- References -- ProbExplainer: A Library for Unified Explainability of Probabilistic Models and an Application in Interneuron Classification -- 1 Introduction -- 2 Background -- 2.1 Probabilistic Models: Bayesian Networks -- 2.2 Existing Software -- 2.3 Interneuron Classification: The Gardener Approach -- 3 Software Framework.
3.1 A Unified Interface -- 3.2 Design of the Algorithms -- 4 Application in GABAergic Interneuron Classification -- 4.1 Data -- 4.2 Experiments -- 4.3 Results -- 5 Conclusions and Future Work -- References -- Interpreting Machine Learning Models for Survival Analysis: A Study of Cutaneous Melanoma Using the SEER Database -- 1 Introduction -- 2 Surveillance, Epidemiology, and End Results Database -- 2.1 Selection of the Individuals -- 2.2 Exploratory Data Analysis -- 3 Machine Learning Models -- 3.1 Data Preprocessing -- 3.2 Machine Learning Models -- 4 Explainability -- 5 Conclusions -- References -- Explanations of Symbolic Reasoning to Effect Patient Persuasion and Education -- 1 Introduction -- 2 Derivation Proofs -- 3 Human-Readable Explanation Generation from Derivation Proofs -- 3.1 Pre-processing Module -- 3.2 Describe Module -- 3.3 Collect Module -- 4 Demonstration -- 5 Planned Evaluation -- 6 Conclusions and Future Work -- References -- International Workshop on Process Mining Applications for Healthcare -- PMApp: An Interactive Process Mining Toolkit for Building Healthcare Dashboards -- 1 Introduction -- 2 Through an Interactive Process Mining Solution for Healthcare -- 3 PMApp: An Interactive Process Mining Toolkit -- 3.1 Experiment Designer -- 3.2 Ingestor Editor -- 3.3 Dashboard -- 4 Discussion and Conclusions -- References -- A Data-Driven Framework for Improving Clinical Managements of Severe Paralytic Ileus in ICU: From Path Discovery, Model Generation to Validation -- 1 Introduction -- 2 Method -- 2.1 Data Resource -- 2.2 Cohort Extraction -- 2.3 Event Log Extraction -- 2.4 Frequent Patient Pathways Discovery -- 2.5 Structural Equation Modelling -- 3 Results -- 4 Discussion and Conclusion -- References -- Phenotypes vs Processes: Understanding the Progression of Complications in Type 2 Diabetes. A Case Study -- 1 Introduction. 2 Methodology -- 2.1 Data Collection and Study Measures -- 2.2 Methods -- 2.3 Data Corpus and Event Log Generation -- 3 Results -- 3.1 Patient-Level Analysis -- 3.2 Short-Term Pathways Analysis -- 4 Discussion -- References -- From Script to Application. A bupaR Integration into PMApp for Interactive Process Mining Research -- 1 Introduction -- 2 Background -- 3 Use Case and Test Scenario -- 3.1 Filtering Cases Based on Activities and Timestamps -- 3.2 Data Augmentation and Conditional Filtering -- 3.3 Manipulation of Activities -- 4 Discussion and Future Work -- References -- Understanding Prostate Cancer Care Process Using Process Mining: A Case Study -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Discussion and Conclusions -- References -- Author Index. |
| Record Nr. | UNINA-9910841872803321 |
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Juarez Jose M
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| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Process mining workshops : ICPM 2021 international workshops, Eindhoven, The Netherlands, October 31 - November 4, 2021 : revised selected papers / / editors, Jorge Muñoz Gama, Xixi Lu
| Process mining workshops : ICPM 2021 international workshops, Eindhoven, The Netherlands, October 31 - November 4, 2021 : revised selected papers / / editors, Jorge Muñoz Gama, Xixi Lu |
| Autore | Munoz-Gama Jorge |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (xiv, 410 pages) : illustrations (chiefly color) |
| Altri autori (Persone) |
Munoz-GamaJorge
LuXixi |
| Collana | Lecture notes in business information processing |
| Soggetto topico |
Data mining
Electronic data processing |
| Soggetto non controllato |
Process Mining
Process Discovery Process Analytics Process Querying Conformance Checking Predictive Process Monitoring Data Science Event Data Streaming Analytics Machine Learning Decision Support Systems Business Process Management Information Systems Petri Nets Open Access |
| ISBN | 3-030-98581-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- XES 2.0 Workshop and Survey -- Rethinking the Input for Process Mining: Insights from the XES Survey and Workshop -- 1 Introduction -- 2 XES Standard: A Brief Overview -- 3 Survey Design and Insights -- 4 Adding Context: Reflections from the XES 2.0 Workshop -- 5 Conclusion -- References -- EdbA 2021: 2nd International Workshop on Event Data and Behavioral Analytics -- Second International Workshop on Event Data and Behavioral Analytics (EdbA'21) -- Organization -- Workshop Chairs -- Program Committee -- Probability Estimation of Uncertain Process Trace Realizations -- 1 Introduction -- 2 Related Work -- 3 Running Example -- 4 Preliminaries -- 5 Method -- 6 Validation of Probability Estimates -- 7 Conclusion -- References -- Visualizing Trace Variants from Partially Ordered Event Data -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Visualizing Trace Variants -- 4.1 Approach -- 4.2 Formal Guarantees -- 4.3 Limitations -- 4.4 Implementation -- 5 Evaluation -- 6 Conclusion -- References -- Analyzing Multi-level BOM-Structured Event Data -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Methods -- 4.1 Analysis Methodology -- 4.2 M2BOM-Structured Assembly Processes -- 5 Case Study -- 6 Conclusion -- References -- Linac: A Smart Environment Simulator of Human Activities -- 1 Introduction -- 2 Existing Solutions -- 3 Proposed Simulation Solution -- 3.1 Configuration of the Smart Environment -- 3.2 Configuration of the Agents' Behavior - AIL Language -- 3.3 Simulation Execution -- 3.4 Clock Simulation -- 3.5 MQTT Output -- 4 Implementation -- 5 Evaluation -- 5.1 Configuration -- 5.2 Results -- 6 Conclusions and Future Works -- References -- Root Cause Analysis in Process Mining with Probabilistic Temporal Logic -- 1 Introduction -- 2 Related Work -- 3 The AITIA-PM Algorithm.
3.1 Background -- 3.2 Algorithmic Procedure -- 4 Demonstration -- 5 Conclusion -- References -- xPM: A Framework for Process Mining with Exogenous Data -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 A Framework for Process Mining with Exogenous Data -- 4.1 Linking -- 4.2 Slicing -- 4.3 Transformation -- 4.4 Discovery -- 4.5 Enhancing -- 5 Evaluation -- 5.1 Procedure -- 5.2 Quality Measures -- 5.3 Event Logs and Exogenous Data -- 5.4 Results and Discussion -- 6 Conclusion -- References -- A Bridging Model for Process Mining and IoT -- 1 Introduction -- 2 Background -- 2.1 IoT Ontologies -- 2.2 Business Process Context Modelling -- 3 Conceptual Ambiguity in IoT and PM -- 3.1 IoT Data -- 3.2 Context in PM vs Context in IoT -- 3.3 Process Event vs IoT Event -- 4 Connecting IoT and Process Mining: A Conceptual Model -- 5 Use Case Validation -- 6 Related Work -- 7 Conclusion -- References -- ML4PM 2021: 2nd International Workshop in Leveraging Machine Learning for Process Mining -- 2nd International Workshop in Leveraging Machine Learning for Process Mining (ML4PM 2021) -- Organization -- Workshop Chairs -- Program Committee -- Additional Reviewers -- Exploiting Instance Graphs and Graph Neural Networks for Next Activity Prediction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Building Instance Graphs -- 3.2 Data Preprocessing -- 3.3 Deep Graph Convolutional Neural Network -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusions and Future Works -- References -- Can Deep Neural Networks Learn Process Model Structure? An Assessment Framework and Analysis -- 1 Introduction -- 2 Related Work -- 3 A Framework for Assessing the Generalisation Capacity of RNNs -- 3.1 The Resampling Procedure -- 3.2 Metrics -- 4 Experimental Evaluation -- 4.1 Process Models -- 4.2 Hyperparameter Search -- 4.3 Results -- 5 Discussion. 6 Conclusion and Future Work -- References -- Remaining Time Prediction for Processes with Inter-case Dynamics -- 1 Introduction -- 2 Preliminaries and Related Work -- 2.1 Related Work -- 2.2 RTM Background -- 2.3 Performance Spectrum with Error Progression -- 3 Approach -- 3.1 Detecting Uncertain Segments -- 3.2 Identifying Inter-case Dynamics in Uncertain Segments -- 3.3 Inter-case Feature Creation -- 3.4 Predicting the Next Segment -- 3.5 Predicting Waiting Time -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Event Log Sampling for Predictive Monitoring -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Proposed Sampling Methods -- 5 Evaluation -- 5.1 Event Logs -- 5.2 Implementation -- 5.3 Evaluation Setting -- 5.4 Experimental Results -- 6 Discussion -- 7 Conclusion -- References -- Active Anomaly Detection for Key Item Selection in Process Auditing -- 1 Introduction -- 2 Related Work -- 2.1 Anomaly Detection -- 2.2 Active Anomaly Detection -- 2.3 Trace Visualisation -- 3 Active Selection Approach -- 3.1 Step One: Encode Process Data -- 3.2 Step Two: Assign Anomaly Score -- 3.3 Step Three: Actively Label Exceptions -- 4 Evaluation -- 4.1 Step One: Encode Process Data -- 4.2 Step Two: Assign Anomaly Score -- 4.3 Step Three: Actively Label Exceptions -- 4.4 Performance Results -- 5 Discussion -- 5.1 Cycle One -- 5.2 Cycle Two -- 5.3 Cycle Three -- 6 Limitations -- 7 Conclusion and Future Work -- References -- Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference Approach -- 1 Introduction -- 2 Background and Related Work -- 2.1 Predictive Process Monitoring -- 2.2 Prescriptive Process Monitoring -- 2.3 Causal Inference -- 3 Approach -- 3.1 Log Preprocessing -- 3.2 Predictive Model -- 3.3 Causal Model -- 3.4 Resource Allocator -- 4 Evaluation -- 4.1 Dataset. 4.2 Experiment Setup -- 4.3 Results -- 4.4 Threats to Validity -- 5 Conclusion -- References -- Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring -- 1 Introduction -- 2 Preliminaries -- 3 Explainability in OOPPM -- 3.1 Explainability Through Interpretability and Faithfulness -- 3.2 Logit Leaf Model -- 3.3 Generalized Logistic Rule Model -- 4 Experimental Evaluation -- 4.1 Benchmark Models -- 4.2 Event Logs -- 4.3 Implementation -- 4.4 Quantitative Metrics Results -- 5 Conclusion -- References -- SA4PM 2021: 2nd International Workshop on Streaming Analytics for Process Mining -- 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) -- Organization -- Workshop Chairs -- Program Committee -- Online Prediction of Aggregated Retailer Consumer Behaviour -- 1 Introduction -- 2 Framework -- 2.1 Features -- 2.2 Clustering -- 2.3 Training -- 2.4 Predicting -- 3 Experimental Evaluation -- 3.1 Experimental Setup -- 3.2 Results -- 4 Related Work -- 5 Conclusion and Future Work -- References -- PErrCas: Process Error Cascade Mining in Trace Streams -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Online Cascade Mining -- 4.1 Outlier Segment-Level Events -- 4.2 Error Cascade Construction -- 4.3 Cascade Patterns -- 5 Evaluation -- 5.1 Synthetic Data -- 5.2 Travel Reimbursement Process -- 6 Conclusion -- References -- Continuous Performance Evaluation for Business Process Outcome Monitoring -- 1 Introduction -- 2 Related Work -- 3 Continuous Prediction Evaluation Framework -- 4 Performance Evaluation Methods -- 4.1 Evaluating Performance Using a Local Timeline -- 4.2 Real-Time Model Performance -- 5 Experimental Analysis and Results -- 6 Conclusions -- References -- PQMI 2021: 6th International Workshop on Process Querying, Manipulation, and Intelligence. 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI 2021) -- Organization -- Workshop Organizers -- Program Committee -- An Event Data Extraction Approach from SAP ERP for Process Mining -- 1 Introduction -- 2 Background -- 2.1 Object-Centric Event Logs -- 2.2 SAP: Entities and Relationships -- 3 Extracting Event Data from SAP ERP: Approach -- 3.1 Building Graphs of Relations -- 3.2 Extracting Object-Centric Event Logs -- 4 Extracting Event Data from SAP ERP: Tool -- 5 Assessment -- 5.1 Building a Graph of Relations -- 5.2 Extracting Object-Centric Event Logs -- 6 Related Work -- 7 Conclusion -- References -- Towards a Natural Language Conversational Interface for Process Mining -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Pre-processing and Tagging -- 3.2 Semantic Parsing -- 3.3 PM Tool Interface Mapping -- 4 Sample Questions -- 5 Proof of Concept -- 6 Conclusions and Future Work -- References -- On the Performance Analysis of the Adversarial System Variant Approximation Method to Quantify Process Model Generalization -- 1 Introduction -- 2 Related Work -- 2.1 Generalization Metric -- 2.2 Adversarial System Variant Approximation -- 3 Notations -- 4 Problem Statement -- 5 Experimental Setup -- 5.1 Sampling Parameter -- 5.2 Variant Log Size -- 5.3 Biased Variant Logs -- 6 Results -- 6.1 Sampling Parameter Results -- 6.2 Variant Log Size Results -- 6.3 Biased Variant Log Results -- 7 Conclusion -- References -- PODS4H 2021: 4th International Workshop on Process-Oriented Data Science for Healthcare -- Fourth International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) -- Organization -- Workshop Chairs -- Program Committee -- Verifying Guideline Compliance in Clinical Treatment Using Multi-perspective Conformance Checking: A Case Study -- 1 Introduction -- 2 Background. 3 Research Method. |
| Record Nr. | UNINA-9910555236103321 |
|
Munoz-Gama Jorge
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Process mining workshops : ICPM 2021 international workshops, Eindhoven, The Netherlands, October 31 - November 4, 2021 : revised selected papers / / editors, Jorge Muñoz Gama, Xixi Lu
| Process mining workshops : ICPM 2021 international workshops, Eindhoven, The Netherlands, October 31 - November 4, 2021 : revised selected papers / / editors, Jorge Muñoz Gama, Xixi Lu |
| Autore | Munoz-Gama Jorge |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (xiv, 410 pages) : illustrations (chiefly color) |
| Altri autori (Persone) |
Munoz-GamaJorge
LuXixi |
| Collana | Lecture notes in business information processing |
| Soggetto topico |
Data mining
Electronic data processing |
| Soggetto non controllato |
Process Mining
Process Discovery Process Analytics Process Querying Conformance Checking Predictive Process Monitoring Data Science Event Data Streaming Analytics Machine Learning Decision Support Systems Business Process Management Information Systems Petri Nets Open Access |
| ISBN | 3-030-98581-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- XES 2.0 Workshop and Survey -- Rethinking the Input for Process Mining: Insights from the XES Survey and Workshop -- 1 Introduction -- 2 XES Standard: A Brief Overview -- 3 Survey Design and Insights -- 4 Adding Context: Reflections from the XES 2.0 Workshop -- 5 Conclusion -- References -- EdbA 2021: 2nd International Workshop on Event Data and Behavioral Analytics -- Second International Workshop on Event Data and Behavioral Analytics (EdbA'21) -- Organization -- Workshop Chairs -- Program Committee -- Probability Estimation of Uncertain Process Trace Realizations -- 1 Introduction -- 2 Related Work -- 3 Running Example -- 4 Preliminaries -- 5 Method -- 6 Validation of Probability Estimates -- 7 Conclusion -- References -- Visualizing Trace Variants from Partially Ordered Event Data -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Visualizing Trace Variants -- 4.1 Approach -- 4.2 Formal Guarantees -- 4.3 Limitations -- 4.4 Implementation -- 5 Evaluation -- 6 Conclusion -- References -- Analyzing Multi-level BOM-Structured Event Data -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Methods -- 4.1 Analysis Methodology -- 4.2 M2BOM-Structured Assembly Processes -- 5 Case Study -- 6 Conclusion -- References -- Linac: A Smart Environment Simulator of Human Activities -- 1 Introduction -- 2 Existing Solutions -- 3 Proposed Simulation Solution -- 3.1 Configuration of the Smart Environment -- 3.2 Configuration of the Agents' Behavior - AIL Language -- 3.3 Simulation Execution -- 3.4 Clock Simulation -- 3.5 MQTT Output -- 4 Implementation -- 5 Evaluation -- 5.1 Configuration -- 5.2 Results -- 6 Conclusions and Future Works -- References -- Root Cause Analysis in Process Mining with Probabilistic Temporal Logic -- 1 Introduction -- 2 Related Work -- 3 The AITIA-PM Algorithm.
3.1 Background -- 3.2 Algorithmic Procedure -- 4 Demonstration -- 5 Conclusion -- References -- xPM: A Framework for Process Mining with Exogenous Data -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 A Framework for Process Mining with Exogenous Data -- 4.1 Linking -- 4.2 Slicing -- 4.3 Transformation -- 4.4 Discovery -- 4.5 Enhancing -- 5 Evaluation -- 5.1 Procedure -- 5.2 Quality Measures -- 5.3 Event Logs and Exogenous Data -- 5.4 Results and Discussion -- 6 Conclusion -- References -- A Bridging Model for Process Mining and IoT -- 1 Introduction -- 2 Background -- 2.1 IoT Ontologies -- 2.2 Business Process Context Modelling -- 3 Conceptual Ambiguity in IoT and PM -- 3.1 IoT Data -- 3.2 Context in PM vs Context in IoT -- 3.3 Process Event vs IoT Event -- 4 Connecting IoT and Process Mining: A Conceptual Model -- 5 Use Case Validation -- 6 Related Work -- 7 Conclusion -- References -- ML4PM 2021: 2nd International Workshop in Leveraging Machine Learning for Process Mining -- 2nd International Workshop in Leveraging Machine Learning for Process Mining (ML4PM 2021) -- Organization -- Workshop Chairs -- Program Committee -- Additional Reviewers -- Exploiting Instance Graphs and Graph Neural Networks for Next Activity Prediction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Building Instance Graphs -- 3.2 Data Preprocessing -- 3.3 Deep Graph Convolutional Neural Network -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusions and Future Works -- References -- Can Deep Neural Networks Learn Process Model Structure? An Assessment Framework and Analysis -- 1 Introduction -- 2 Related Work -- 3 A Framework for Assessing the Generalisation Capacity of RNNs -- 3.1 The Resampling Procedure -- 3.2 Metrics -- 4 Experimental Evaluation -- 4.1 Process Models -- 4.2 Hyperparameter Search -- 4.3 Results -- 5 Discussion. 6 Conclusion and Future Work -- References -- Remaining Time Prediction for Processes with Inter-case Dynamics -- 1 Introduction -- 2 Preliminaries and Related Work -- 2.1 Related Work -- 2.2 RTM Background -- 2.3 Performance Spectrum with Error Progression -- 3 Approach -- 3.1 Detecting Uncertain Segments -- 3.2 Identifying Inter-case Dynamics in Uncertain Segments -- 3.3 Inter-case Feature Creation -- 3.4 Predicting the Next Segment -- 3.5 Predicting Waiting Time -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Event Log Sampling for Predictive Monitoring -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Proposed Sampling Methods -- 5 Evaluation -- 5.1 Event Logs -- 5.2 Implementation -- 5.3 Evaluation Setting -- 5.4 Experimental Results -- 6 Discussion -- 7 Conclusion -- References -- Active Anomaly Detection for Key Item Selection in Process Auditing -- 1 Introduction -- 2 Related Work -- 2.1 Anomaly Detection -- 2.2 Active Anomaly Detection -- 2.3 Trace Visualisation -- 3 Active Selection Approach -- 3.1 Step One: Encode Process Data -- 3.2 Step Two: Assign Anomaly Score -- 3.3 Step Three: Actively Label Exceptions -- 4 Evaluation -- 4.1 Step One: Encode Process Data -- 4.2 Step Two: Assign Anomaly Score -- 4.3 Step Three: Actively Label Exceptions -- 4.4 Performance Results -- 5 Discussion -- 5.1 Cycle One -- 5.2 Cycle Two -- 5.3 Cycle Three -- 6 Limitations -- 7 Conclusion and Future Work -- References -- Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference Approach -- 1 Introduction -- 2 Background and Related Work -- 2.1 Predictive Process Monitoring -- 2.2 Prescriptive Process Monitoring -- 2.3 Causal Inference -- 3 Approach -- 3.1 Log Preprocessing -- 3.2 Predictive Model -- 3.3 Causal Model -- 3.4 Resource Allocator -- 4 Evaluation -- 4.1 Dataset. 4.2 Experiment Setup -- 4.3 Results -- 4.4 Threats to Validity -- 5 Conclusion -- References -- Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring -- 1 Introduction -- 2 Preliminaries -- 3 Explainability in OOPPM -- 3.1 Explainability Through Interpretability and Faithfulness -- 3.2 Logit Leaf Model -- 3.3 Generalized Logistic Rule Model -- 4 Experimental Evaluation -- 4.1 Benchmark Models -- 4.2 Event Logs -- 4.3 Implementation -- 4.4 Quantitative Metrics Results -- 5 Conclusion -- References -- SA4PM 2021: 2nd International Workshop on Streaming Analytics for Process Mining -- 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) -- Organization -- Workshop Chairs -- Program Committee -- Online Prediction of Aggregated Retailer Consumer Behaviour -- 1 Introduction -- 2 Framework -- 2.1 Features -- 2.2 Clustering -- 2.3 Training -- 2.4 Predicting -- 3 Experimental Evaluation -- 3.1 Experimental Setup -- 3.2 Results -- 4 Related Work -- 5 Conclusion and Future Work -- References -- PErrCas: Process Error Cascade Mining in Trace Streams -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Online Cascade Mining -- 4.1 Outlier Segment-Level Events -- 4.2 Error Cascade Construction -- 4.3 Cascade Patterns -- 5 Evaluation -- 5.1 Synthetic Data -- 5.2 Travel Reimbursement Process -- 6 Conclusion -- References -- Continuous Performance Evaluation for Business Process Outcome Monitoring -- 1 Introduction -- 2 Related Work -- 3 Continuous Prediction Evaluation Framework -- 4 Performance Evaluation Methods -- 4.1 Evaluating Performance Using a Local Timeline -- 4.2 Real-Time Model Performance -- 5 Experimental Analysis and Results -- 6 Conclusions -- References -- PQMI 2021: 6th International Workshop on Process Querying, Manipulation, and Intelligence. 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI 2021) -- Organization -- Workshop Organizers -- Program Committee -- An Event Data Extraction Approach from SAP ERP for Process Mining -- 1 Introduction -- 2 Background -- 2.1 Object-Centric Event Logs -- 2.2 SAP: Entities and Relationships -- 3 Extracting Event Data from SAP ERP: Approach -- 3.1 Building Graphs of Relations -- 3.2 Extracting Object-Centric Event Logs -- 4 Extracting Event Data from SAP ERP: Tool -- 5 Assessment -- 5.1 Building a Graph of Relations -- 5.2 Extracting Object-Centric Event Logs -- 6 Related Work -- 7 Conclusion -- References -- Towards a Natural Language Conversational Interface for Process Mining -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Pre-processing and Tagging -- 3.2 Semantic Parsing -- 3.3 PM Tool Interface Mapping -- 4 Sample Questions -- 5 Proof of Concept -- 6 Conclusions and Future Work -- References -- On the Performance Analysis of the Adversarial System Variant Approximation Method to Quantify Process Model Generalization -- 1 Introduction -- 2 Related Work -- 2.1 Generalization Metric -- 2.2 Adversarial System Variant Approximation -- 3 Notations -- 4 Problem Statement -- 5 Experimental Setup -- 5.1 Sampling Parameter -- 5.2 Variant Log Size -- 5.3 Biased Variant Logs -- 6 Results -- 6.1 Sampling Parameter Results -- 6.2 Variant Log Size Results -- 6.3 Biased Variant Log Results -- 7 Conclusion -- References -- PODS4H 2021: 4th International Workshop on Process-Oriented Data Science for Healthcare -- Fourth International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) -- Organization -- Workshop Chairs -- Program Committee -- Verifying Guideline Compliance in Clinical Treatment Using Multi-perspective Conformance Checking: A Case Study -- 1 Introduction -- 2 Background. 3 Research Method. |
| Record Nr. | UNISA-996464540703316 |
|
Munoz-Gama Jorge
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||