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Research
We apply methods from computational learning, machine learning, data mining, database algorithmics and formal logic to the design of innovative algorithms and systems for data analysis and prediction.
Our mission is to develop practical solutions from sound principles.
Research highlights:
1. Data mining and machine learning
- predictive and explanatory models
- recommending systems
- knowledge discovery in data
- computational learning theory
People involved: Marta Arias, Argimiro Arratia, Jaume Baixeries, José L. Balcázar, Santiago Boza, Jorge Castro, Ricard Gavaldà, Josefina López, Ariadna Quattoni, Borja Balle, Bernardino Casas, Joan Garriga
2. Massive data analysis with emphasis on data streams
- efficient algorithms, scalability
- real-time analytics
- mining with limited resources
People involved: Marta Arias, José L. Balcázar, Jorge Castro, Ricard Gavaldà, Borja Balle, Alberto Lumbreras, Ramon Xuriguera
3. Analysis of structured data
- sequences, trees, graphs, relational data, linguistic data, XML analysis
- networks and the web: social networks, communities
- applications of data mining and learning to energy-efficient computing (green computing)
People involved: Marta Arias, Jaume Baixeries, José L. Balcázar, Jorge Castro, Jordi Delgado, Ricard Gavaldà, Ariadna Quattoni, Josep Ll. Berral, Alberto Lumbreras, Ramon Xuriguera
4. Mathematical linguistics
- logic-based approaches to linguistic analysis
- quantitative linguistics
- language evolution and acquisition
People involved: Jordi Delgado, Glyn Morrill, Josefina Sierra, Pau Fernández
