The IRIS team conducts research activities to define Information Retrieval (IR) models that address multiple issues. The team is particularly interested in complex information retrieval where it is necessary to consider different elements depending on the context in which the search is conducted (i.e., contextual IR).

The IRIS team is also working on the development of value-added information. In particular, it defines models for building information that meets a given need by aggregating relevant information nuggets from different heterogeneous sources, such as the Web or scientific publications. The representation of data in the form of networks, often dynamic, appears natural in many cases: social networks, word networks, social networks, the Web. It is in this context that the IRIS team is interested in the mining of dynamic graphs to better understand or predict the relationships between entities.

The IRIS team also conducts research in bibliometrics and more generally in scientometrics.

This research is multidisciplinary and conducted in collaboration with researchers from disciplines such as sociology, psychology, pharmacology or biology. The IT issues to which the team responds are thus enriched by issues from multiple disciplines, thus opening up new lines of research.

The work of the IRIS team is naturally in line with current issues related to Data Science.