قـسـم «معلومات و تعلم اصطناعي»

مسؤول :

Bernd Amann Campus Pierre et Marie Curie 25-26/506

تقديـم مـخـتـصـر

The DAPA Data and Knowledge Science research department is composed of four research teams (MLIA, LFI, ACASA, BD) with about 25 permanent members. Its research is focused on all kinds of information processing and analysis problems and 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)

Theoretical and applied contributions cover a wide spectrum of methods from machine learning, artificial intelligence and databases applied to different types of information (web, text, images, videos, graphs, trees). Projects and research contracts deal with data and knowledge-centric applications like social networks, internet of things, smart transportation and digital humanities:

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.

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الأرشـيف

للاتصال

bernd.amann (at) nulllip6.fr