The online activity of users produces a huge volume of behavioural data, which can be processed to provide useful knowledge and applications that make digital spaces more convenient, safe and impactful. This involves a range of methods, mostly based on AI.
In the Web and User Data Processing group, we combat false information and online malicious behaviour. We strive to create an extensive infrastructure for collecting online content in large volumes. This content is then monitored by AI-based methods to detect signs of false information and online malicious behaviour. We also make use of information retrieval and recommendations, mostly for e-commerce applications. Our research delivers innovative methods that improve customer experience and business goals. These methods can also reveal connections in our partners’ data to improve their processes and offer personalized services to their customers.
RESEARCH AREAS OF INTEREST:
- Misinformation analysis and characterization
- Machine learning based detection and prediction methods
- Interpretation and explanation of machine learning models
- User behaviour modelling and segmentation