163 citations · 266 across the 9 of their papers we have counts for
9 papers
Efficient pattern-based anomaly detection in a network of multivariate devices
Len Feremans, Boris Cule, Bart Goethals
Many organisations manage service quality and monitor a large set devices and servers where each entity is associated with telemetry or physical sensor data series. Recently, vario…
Modelling Users with Item Metadata for Explainable and Interactive Recommendation
Joey De Pauw, Koen Ruymbeek, Bart Goethals
Recommender systems are used in many different applications and contexts, however their main goal can always be summarised as "connecting relevant content to interested users". Per…
Proximity Forest: An effective and scalable distance-based classifier for time series
Benjamin Lucas, Ahmed Shifaz, Charlotte Pelletier +5
Research into the classification of time series has made enormous progress in the last decade. The UCR time series archive has played a significant role in challenging and guiding…
Understanding Concept Drift
Geoffrey I. Webb, Loong Kuan Lee, François Petitjean +1
Concept drift is a major issue that greatly affects the accuracy and reliability of many real-world applications of machine learning. We argue that to tackle concept drift it is im…
Relational Association Rules: getting WARMeR
Bart Goethals, Jan Van den Bussche
In recent years, the problem of association rule mining in transactional data has been well studied. We propose to extend the discovery of classical association rules to the discov…
Mining All Non-Derivable Frequent Itemsets
Toon Calders, Bart Goethals
Recent studies on frequent itemset mining algorithms resulted in significant performance improvements. However, if the minimal support threshold is set too low, or the data is high…