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DUKe - Data User Knowledge

Interactive (Human in the loop) Machine Learning, Data mining or exploration

Coordinator : Philippe LERAY  
Responsable adjoint : Guillaume RASCHIA  
Area(s) of expertise :
SIEL
SDD

The DUKe (Data User Knowledge) research group, part of the LS2N laboratory (UMR CNRS 6004), University of Nantes, aims at proposing querying, mining and learning techniques that take into account

  • data types (relational, spatial, graphical, temporal, stream, etc.),
  • expert knowledge or user interactions through adapted visual supports

Moreover, the objective of the research team is to provide algorithms that 

  • consider user-related data, in particular issues like privacy, fairness and the value of personal data
  • show good properties in terms of user interaction : anytime, incremental, fast, user-knowledge accounting or graphical representation
  • allow to observe, analyze users' usage and then propose a user-system coevolution

Part of our work has, over the years, established connections with other research fields that handle large data sets, which analysis requires introduction of field-specific expert knowledge into models (biology, ethology, history, sociology, literature and education sciences).

The DUKe research group was created in jan. 2014 by merging the former COD and GRIM research groups.

Team topics

Our goal is to propose User-centered methods for Data management, Mining or Machine Learning. This involves four challenges


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