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Conformance Checking and Diagnosis in Process Mining : Comparing Observed and Modeled Processes / / by Jorge Munoz-Gama
| Conformance Checking and Diagnosis in Process Mining : Comparing Observed and Modeled Processes / / by Jorge Munoz-Gama |
| Autore | Munoz-Gama Jorge |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XIV, 202 p. 90 illus.) |
| Disciplina | 658.054 |
| Collana | Lecture Notes in Business Information Processing |
| Soggetto topico |
Information technology - Management
Data mining Computer Application in Administrative Data Processing Business Process Management Data Mining and Knowledge Discovery |
| ISBN | 3-319-49451-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- 1.1 Processes, Models, and Data -- 1.2 Process Mining -- 1.3 Conformance Checking Explained: The University Case -- 1.4 Book Outline -- Part I Conformance Checking in Process Mining -- 2 Conformance Checking and its Challenges -- 2.1 The Role of Process Models in Conformance Checking -- 2.2 Dimensions of Conformance Checking -- 2.3 Replay-based and Align-based Conformance Checking -- 2.4 Challenges of Conformance Checking -- 3 Conformance Checking and its Elements -- 3.1 Basic Notations -- 3.2 Event Log -- 3.3 Process Models -- 3.4 Process Modeling Formalisms -- 3.4.1 Petri Nets -- 3.4.2 Workflow Nets -- 3.4.3 Other Formalisms -- Part II Precision in Conformance Checking -- 4 Precision in Conformance Checking -- 4.1 Precision: The Forgotten Dimension -- 4.2 The Importance of Precision -- 4.3 Measures of Precision -- 4.4 Requirements for Precision -- 5 Measuring Precision -- 5.1 Precision based on Escaping Arcs -- 5.2 Constructing the Observed Behavior -- 5.3 Incorporating Modeled Behavior -- 5.4 Detecting Escaping Arcs and Evaluating Precision -- 5.5 Minimal Imprecise Traces -- 5.6 Limitations and Extensions -- 5.6.1 Unfitting Scenario -- 5.6.2 Indeterministic Scenario -- 5.7 Summary -- 6 Evaluating Precision in Practice -- 6.1 The University Case: The Appeals Process -- 6.2 Experimental Evaluation -- 7 Handling Noise and Incompleteness -- 7.1 Introduction -- 7.2 Robustness on the Precision -- 7.3 Confidence on Precision.-7.3.1 Upper Confidence Value -- 7.3.2 Lower Confidence Value -- 7.4 Experimental Results -- 7.5 Summary -- 8 Assessing Severity -- 8.1 Introduction -- 8.2 Severity of an Escaping Arc -- 8.2.1 Weight of an Escaping Arc -- 8.2.2 Alternation of an Escaping Arc -- 8.2.3 Stability of an Escaping Arc -- 8.2.4 Criticality of an Escaping Arc -- 8.2.5 Visualizing the Severity -- 8.2.6 Addressing Precision Issues based on Severity -- 8.3 Experimental Results -- 8.4 Summary -- 9 Handling non-Fitness -- 9.1 Introduction -- 9.2 Cost-Optimal Alignment -- 9.3 Precision based on Alignments -- 9.4 Precision from 1-Alignment -- 9.5 Summary -- 10 Alternative and Variants to Handle non-Fitness -- 10.1 Precision from All-Alignment -- 10.2 Precision from Representative-Alignment -- 10.3 Abstractions for the Precision based on Alignments -- 10.3.1 Abstraction on the Order -- 10.3.2 Abstraction on the Direction -- 10.4 Summary -- 11 Handling non-Fitness in Practice -- 11.1 The University Case: The Exchange Process -- 11.2 Experimental Results -- Part III Decomposition in Conformance Checking -- 12 Decomposing Conformance Checking. -12.1 Introduction -- 12.2 Single-Entry Single-Exit and Refined Process Structure Tree -- 12.3 Decomposing Conformance Checking using SESEs -- 12.4 Summary -- 13 Decomposing for Fitness Checking -- 13.1 Introduction -- 13.2 Bridging a Valid Decomposition -- 13.3 Decomposition with invisible/duplicates -- 13.4 Summary -- 14 Decomposing Conformance Checking in Practice -- 14.1 The Bank Case: The Transaction Process -- 14.2 Experimental Results -- 15 Diagnosing Conformance -- 15.1 Introduction -- 15.2 Topological Conformance Diagnosis -- 15.3 Multi-level Conformance Diagnosis and its Applications -- 15.3.1 Stand-alone Checking -- 15.3.2 Multi-Level Analysis -- 15.3.3 Filtering -- 15.4 Experimental Results -- 15.5 Summary -- 16 Data-aware Processes and Alignments -- 16.1 Introduction -- 16.2 Data-aware Processes -- 16.2.1 Petri nets with Data -- 16.2.2 Event Logs and Relating Models to Event Logs -- 16.2.3 Data Alignments -- 16.3 Summary -- 17 Decomposing Data-aware Conformance -- 17.1 Introduction -- 17.2 Valid Decomposition of Data-aware Models -- 17.3 SESE-based Strategy for a Valid Decomposition -- 17.4 Implementation and Experimental Results -- 17.5 Summary -- 18 Event-based Real-time Decomposed Conformance Checking -- 18.1 Introduction -- 18.2 Event-based Real-time Decomposed Conformance -- 18.2.1 Model and Log Decomposition -- 18.2.2 Event-based Heuristic Replay -- 18.3 Experimental Results -- 18.4 Summary -- Part IV Conclusions and Future Work -- 19 Conclusions -- 19.1 Conclusion and Reflection -- 19.2 Summary of Contributions -- 19.3 Challenges and Directions for Future Work -- References. |
| Record Nr. | UNINA-9910255004603321 |
Munoz-Gama Jorge
|
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| 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. | UNISA-996464540703316 |
|
Munoz-Gama Jorge
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Process Mining Workshops : ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers / / edited by Jorge Munoz-Gama, Xixi Lu
| Process Mining Workshops : ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers / / edited by Jorge Munoz-Gama, Xixi Lu |
| Autore | Munoz-Gama Jorge |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (xiv, 410 pages) : illustrations (chiefly color) |
| Disciplina | 006.312 |
| Altri autori (Persone) |
Munoz-GamaJorge
LuXixi |
| Collana | Lecture Notes in Business Information Processing |
| Soggetto topico |
Data mining
Information technology - Management Data Mining and Knowledge Discovery Business Process Management Computer Application in Administrative Data Processing Accés obert Mineria de dades Tecnologia de la informació Gestió de la informació Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-98581-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Rethinking the Input for Process Mining: Insights from the XES Survey and Workshop -- Probability Estimation of Uncertain Process Trace Realizations -- Visualizing Trace Variants From Partially Ordered Event Data -- Analyzing Multi-level BOM-structured Event Data -- Linac: A Smart Environment Simulator of Human Activities -- Root Cause Analysis in Process Mining with Probabilistic Temporal Logic -- xPM: A Framework for Process Mining with Exogenous Data -- A Bridging Model for Process Mining and IoT -- Exploiting Instance Graphs and Graph Neural Networks for next activity prediction -- Can deep neural networks learn process modelstructure? An assessment framework and analysis -- Remaining Time Prediction for Processes with Inter-Case Dynamics -- Event Log Sampling for Predictive Monitoring -- Active Anomaly Detection for Key Item Selection in Process Auditing -- Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference Approach -- Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring -- Online Prediction of Aggregated Retailer Consumer Behaviour -- PErrCas: Process Error Cascade Mining in Trace Streams -- Continuous performance evaluation for business process outcome monitoring -- An Event Data Extraction Approach from SAP ERP for Process Mining -- Towards a Natural Language Conversational Interface for Process Mining -- On the Performance Analysis of the Adversarial System Variant Approximation Method to Quantify Process Model Generalization -- Verifying guideline compliance in clinical treatment using multi-perspective conformance checking: a case study -- Patient Discharge Classification based on the Hospital Treatment Process -- Combining the Clinical and Operational Perspectives in Heterogeneous Treatment E ect Inference in Healthcare Processes -- Interactive Process Mining Applied in a Cardiology Outpatient Department -- Discovering care pathways for multi-morbid patients using event graphs -- Process Mining in Trusted Execution Environments: Towards Hardware Guarantees for Trust-aware Inter-organizational Process Analysis -- Quantifying the Re-identification Risk in Published Process Models -- Trustworthy Artificial Intelligence and Process Mining: Challenges and Opportunities. |
| Record Nr. | UNINA-9910555236103321 |
|
Munoz-Gama Jorge
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||