«Databases and machine learning» Department
Team leader :
Bernd Amann Site Jussieu 25-26/506
The research of the Data and Machine Learning (DAPA) develops a greater understanding of all kinds of aspects concerning the modeling, analysis, and information and knowledge processing. Its activites focus in particular recent challenges in "Data and Knowledge Science" and "Big Data".
- Statistical and symbolic machine Learning (MLIA, LFI, ACASA)
- Computational intelligence and fuzzy logic (LFI, ACASA)
- Information retrieval (text, image, multimedia, streams) (MLIA, LFI, BD)
- Knowledge Representation and deasoning (LFI, ACASA)
- Heterogeneous, distributed and dynamic databases (BD)
- Cognitive sciences and digital humanities (ACASA)
- Recommendation, collaborative filtering and information personalization (MLIA, LFI, ACASA, BD)
Theoratical and applied contributions cover a wide spectrum of information (text, images, videos, graphs, trees, probabilistic data) and methods from the machine learning (Bayesian networks), the artificial intelligence (based learning explanation and meta-knowledge, fuzzy logic) and the database (indexing, storage, query optimization) domains.
Projects and research contracts deal with many applications ranging from adaptive and selective information retrieval to data management in large scale networks:
- Online and offline analysis of social networks
- Intelligent transport and mobility
- Web archiving
- Continuous filtering and aggregation of information streams
- Stylistic text analysis
Data and knowledge science, statistical and symbolic machine learning, fuzzy logic, information fusion, content based information retrieval, social media, computational intelligence, streaming information, user interaction and modelling, risk analysis, distributed databases, data replication and load balancing, web archives.
bernd.amann (at) nulllip6.fr