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Intelligent systems are characterized by learning processes that allow the acquisition of new skills and deal with a large amount of heterogeneous, uncertain and probabilistic data. Due to the complexity of the real-world situations represented by them, the automatic abstraction of information from data, the formation of appropriate representative models, and the semantic processing of existing information is essential to build intelligent systems for digital transformation, such as mobility To enable industry, medicine and education.

Projekte

Cleopatra

Cross-lingual Event-centric Open Analytics Research Academy

Data4UrbanMobility

Data4UrbanMobility focuses on facilitating innovative mobility services and mobility-related infrastructure development in smart cities through comprehensive data analytics

Discovering Job Knowledge from Web Data

Discovering Job Knowledge from Web Data

ErrorlessLearning

Project extention for a orthograhic training methode

InclusiveOCW

Inclusive, collaborative creation and usage of open courseware in the professional promotion of people with visual impairments

Interpreting Neural Rankers

Understanding decisions made by Deep Learned Models in Information Retrieval
(Amazon Research Grant)

Managed Forgetting

Die heutige Informationsflut erschwert es immer mehr, sich auf die wirklich relevanten und wichtigen Dinge zu konzentrieren

OSCAR

Opinion Stream Classification with Ensembles and Active learners

Regio

 A mapping of the origin and success of cooperation relationships in regional research networks and innovation clusters 

Development of an intelligent algorithm in order to reduce the return rate in the B2B context of fashion eCommerce