Evaluation Goals for Online Process Mining: A Concept Drift Perspective | 1 | 0.36 | 2022 |
On the use of online clustering for anomaly detection in trace streams. | 0 | 0.34 | 2021 |
Process Mining Encoding via Meta-learning for an Enhanced Anomaly Detection | 0 | 0.34 | 2021 |
Language-Independent Fake News Detection: English, Portuguese, and Spanish Mutual Features. | 1 | 0.36 | 2020 |
The CDESF Toolkit - An Introduction. | 0 | 0.34 | 2020 |
Evaluating Trace Encoding Methods in Process Mining. | 0 | 0.34 | 2020 |
Analysis of Language Inspired Trace Representation for Anomaly Detection. | 0 | 0.34 | 2020 |
Anomaly Detection on Event Logs with a Scarcity of Labels | 0 | 0.34 | 2020 |
Comparing Concept Drift Detection with Process Mining Tools | 0 | 0.34 | 2019 |
Deciding among Fake, Satirical, Objective and Legitimate news: A multi-label classification system | 0 | 0.34 | 2019 |
Overlapping Analytic Stages in Online Process Mining | 1 | 0.36 | 2019 |
A Framework for Human-in-the-loop Monitoring of Concept-drift Detection in Event Log Stream. | 2 | 0.37 | 2018 |
Detection of Human, Legitimate Bot, and Malicious Bot in Online Social Networks Based on Wavelets. | 1 | 0.35 | 2018 |
User Classification on Online Social Networks by Post Frequency. | 0 | 0.34 | 2017 |
A Framework for Trace Clustering and Concept-drift Detection in Event Streams. | 0 | 0.34 | 2017 |