Research Topics
Underlying topics in Big Data. For applied topics see expertise.
- Anomaly Detection
- Big Data Analytics (Bart Baesens)
- Big Data Storage &Amp; Integration (Wilfried Lemahieu)
- Classification
- Clustering
- Complex Networks (Johan Suykens)
- Cryptocurrencies &Amp; Blockchain (Jochen De Weerdt)
- Data &Amp; Process Science (Seppe vanden Broucke)
- Data Fusion
- Data Modeling &Amp; Semantics (Wilfried Lemahieu)
- Data Quality (Wilfried Lemahieu)
- Data Visualization
- Data-Driven Modelling (Johan Suykens)
- Deep Learning (Johan Suykens)
- Dimensionality Reduction
- Kernel Methods (Johan Suykens)
- Knowledge Management (Jan Vanthienen)
- Learning With Tensors (Johan Suykens)
- Local Pattern Mining
- Machine Learning (Seppe vanden Broucke)
- Marketing Analytics (Bart Baesens)
- Neural Networks (Johan Suykens)
- Predictive Analytics (Seppe vanden Broucke)
- Process Analytics (Seppe vanden Broucke)
- Process Mining (Jochen De Weerdt)
- Rule-Based Systems (Jan Vanthienen)
- Social Network Analytics (Bart Baesens)
- Sparse Modelling (Johan Suykens)
- Spatio-Temporal Data Analysis
- Supervised Machine Learning
- Support Vector Machines
- Tensors
- Topological Data Analysis
- Unsupervised Machine Learning
- Visual Analytics