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

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).

Our current application fields are :

• Enterprise of the future
  • Business Intelligence : customer relationship management, ...
  • Manufacturing intelligence : predictive maintenance, ...
  • Digital transformation : extraction and formalization of business knowledge
• Health of the future
  • Personalized medicine : genome-wide association studies, ...
  • Hospital of the future : treatment and immersion in virtual reality, ...
• Digital Humanities
  • Learning Analytics : Mooc log mining, recommendation of teaching resources, ...
  • Cultural heritage : helping historical resources annotation, recommendation of museographic resources ...
  • Sociology, epistemology : cross-mining of digital traces, surveys and interviews

Thématiques de l'équipe