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Found 13 papers, 5 papers with code
INEXA: Interactive and Explainable Process Model Abstraction Through Object-Centric Process Mining
To enable the exploration of discovered process models at different granularity levels, we propose INEXA, an interactive, explainable process model abstraction method that keeps the link to the event log.
Analyzing An After-Sales Service Process Using Object-Centric Process Mining: A Case Study
Process mining, a technique turning event data into business process insights, has traditionally operated on the assumption that each event corresponds to a singular case or object.
Extracting Rules from Event Data for Study Planning
In this study, we examine how event data from campus management systems can be used to analyze the study paths of higher education students.
Preventing Object-centric Discovery of Unsound Process Models for Object Interactions with Loops in Collaborative Systems: Extended Version
Similar to classical process discovery, where we aim for behaviorally sound process models as a result, in OCPD, we aim for soundness of the resulting object-centric Petri nets.
Performance-Preserving Event Log Sampling for Predictive Monitoring
Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances.
Explainable Predictive Decision Mining for Operational Support
By predicting the decision, one can take proactive actions to improve the process.
Monitoring Constraints in Business Processes Using Object-Centric Constraint Graphs
Existing techniques for constraint monitoring assume that a single case notion exists in a business process, e. g., a patient in a healthcare process, and each event is associated with the case notion.
A Framework for Extracting and Encoding Features from Object-Centric Event Data
The flattening process is lossy, leading to inaccurate features extracted from flattened data.
Detecting Context-Aware Deviations in Process Executions
We have implemented the proposed framework as a web service that can be extended to various contexts and deviation detection methods.
OPerA: Object-Centric Performance Analysis
Performance analysis in process mining aims to provide insights on the performance of a business process by using a process model as a formal representation of the process.
Event Log Sampling for Predictive Monitoring
Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances.
Analyzing Process-Aware Information System Updates Using Digital Twins of Organizations
In this paper, we use the recently developed Digital Twins of Organizations (DTOs) to assess the impact of (process-aware) information systems updates.
Prediction-based Resource Allocation using Bayesian Neural Networks and Minimum Cost and Maximum Flow Algorithm
Predictive business process monitoring aims at providing predictions about running instances by analyzing logs of completed cases in a business process.
