172 results on '"Dirk Fahland"'
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2. Decomposing Process Performance based on Actor Behavior.
3. Discovery of Object-Centric Declarative Models.
4. Multi-perspective Concept Drift Detection: Including the Actor Perspective.
5. Process Mining from Jira Issues at a Large Company.
6. Why are my Pizzas late?
7. The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them.
8. Inferring Missing Entity Identifiers from Context Using Event Knowledge Graphs.
9. Event Knowledge Graphs for Auditing: A Case Study.
10. Implementing Object-Centric Event Data Models in Event Knowledge Graphs.
11. Multi-dimensional Process Analysis.
12. Aggregating Event Knowledge Graphs for Task Analysis.
13. Discover Context-Rich Local Process Models (Extended Abstract).
14. Generating event logs with CPN IDE.
15. Object-Centric Process Mining (and more) using a Graph-Based Approach with PromG.
16. Classifying and Detecting Task Executions and Routines in Processes Using Event Graphs.
17. Process Discovery Using Graph Neural Networks.
18. Striking a new Balance in Accuracy and Simplicity with the Probabilistic Inductive Miner.
19. Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources.
20. Visualizing Token Flows Using Interactive Performance Spectra.
21. Defining meaningful Local Process Models.
22. Multi-Dimensional Performance Analysis and Monitoring Using Integrated Performance Spectra.
23. Detecting System-Level Behavior Leading To Dynamic Bottlenecks.
24. Identifying and Reducing Errors in Remaining Time Prediction due to Inter-Case Dynamics.
25. Prozessmanagement und Process-Mining: Grundlagen
26. Describing Behavior of Processes with Many-to-Many Interactions.
27. Storing and Querying Multi-dimensional Process Event Logs Using Graph Databases.
28. Performance Mining for Batch Processing Using the Performance Spectrum.
29. Predictive Performance Monitoring of Material Handling Systems Using the Performance Spectrum.
30. Unbiased, Fine-Grained Description of Processes Performance from Event Data.
31. The Performance Spectrum Miner: Visual Analytics for Fine-Grained Performance Analysis of Processes.
32. Who Is Behind the Model? Classifying Modelers Based on Pragmatic Model Features.
33. Semi-supervised Log Pattern Detection and Exploration Using Event Concurrence and Contextual Information.
34. A Conceptual Framework for Understanding Event Data Quality for Behavior Analysis.
35. A Visualization of Human Physical Risks in Manufacturing Processes Using BPMN.
36. Discovering Interacting Artifacts from ERP Systems (Extended Abstract).
37. Automating Data Exchange in Process Choreographies (Extended Abstract).
38. Dynamic Skipping and Blocking and Dead Path Elimination for Cyclic Workflows.
39. Interactively Exploring Logs and Mining Models with Clustering, Filtering, and Relabeling.
40. Handling Duplicated Tasks in Process Discovery by Refining Event Labels.
41. Scalable Process Discovery with Guarantees.
42. Detecting Deviating Behaviors Without Models.
43. Using Life Cycle Information in Process Discovery.
44. Supervised learning of process discovery techniques using graph neural networks
45. Conformance checking in healthcare based on partially ordered event data.
46. Compliance Checking of Data-Aware and Resource-Aware Compliance Requirements.
47. Discovering Block-Structured Process Models from Incomplete Event Logs.
48. Automating Data Exchange in Process Choreographies.
49. Conformance Checking Based on Partially Ordered Event Data.
50. Exploring Processes and Deviations.
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