Search Results for author:
Found 8 papers, 2 papers with code
People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection
CADs introduce minimal changes to existing training data points and flip their labels; training on them may reduce model dependency on spurious features.
Tailoring Machine Learning for Process Mining
Machine learning models are routinely integrated into process mining pipelines to carry out tasks like data transformation, noise reduction, anomaly detection, classification, and prediction.
A Combined Approach of Process Mining and Rule-based AI for Study Planning and Monitoring in Higher Education
This paper presents an approach of using methods of process mining and rule-based artificial intelligence to analyze and understand study paths of students based on campus management system data and study program models.
Feature Recommendation for Structural Equation Model Discovery in Process Mining
Considering the volume of the data and the number of features captured by the information system of today's companies, the task of discovering the set of features that should be considered in root cause analysis can be quite involving.
Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP)
In the DFG-funded Cluster of Excellence "Internet of Production" (IoP), process mining is used to create "digital shadows" to improve a wide variety of operational processes.
Case Level Counterfactual Reasoning in Process Mining
This is the reason we advocate the use of structural equation models and counterfactual reasoning.
Efficient Logging for Blockchain Applications
Second generation blockchain platforms, like Ethereum, can store arbitrary data and execute user-defined smart contracts.
Software Engineering
Fairness-Aware Process Mining
In this paper, we present a solution to this problem by creating a fair classifier for such situations.
