Frederic Stahl
German Research Centre for Artificial Intelligence(DE)
Publications by Year
Research Areas
Data Stream Mining Techniques, Data Mining Algorithms and Applications, Machine Learning and Data Classification, Anomaly Detection Techniques and Applications, Network Security and Intrusion Detection
Most-Cited Works
- → Machine learning for aquatic plastic litter detection, classification and quantification (APLASTIC-Q)(2020)116 cited
- → A rule dynamics approach to event detection in Twitter with its application to sports and politics(2016)75 cited
- → Scalable real-time classification of data streams with concept drift(2017)75 cited
- → A heterogeneous online learning ensemble for non-stationary environments(2019)52 cited
- → Categorization and Construction of Rule Based Systems(2014)48 cited
- → Data stream mining in ubiquitous environments: state‐of‐the‐art and current directions(2014)46 cited
- → Towards cost-sensitive adaptation: When is it worth updating your predictive model?(2014)40 cited
- → An overview of the use of neural networks for data mining tasks(2012)39 cited
- → Real-time feature selection technique with concept drift detection using adaptive micro-clusters for data stream mining(2018)37 cited
- → Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments(2010)34 cited