The "decision aiding" axis aims to help one or more individuals, confronted with complex decision alternatives, possibly described by multiple conflicting consequences, to make decisions by providing them with appropriate support tools.
This axis is currently divided into 4 themes : the modelling and the elicitation of preferences, multi-criteria decision aiding, recommender systems, and geographical information science.
The "data mining" axis deals with the extraction of knowledge from large quantities of data (either structured, or partially structured) via automatic or semi-automatic methods.
This axis is currently divided into 4 themes : the search for frequent and regular items, the analysis of texts, graph mining, and, data visualisation, involving the difficulties linked to the synthesis of high dimensional data.
The "information integration and quality" axis focuses on the agregation and the quality of data and information originating from heterogeneous sources.
More specifically, the team is interested in various measures of the quality of this aggregated information, in the relevance of the descriptors of visual content, in the quality of the information in accordance with the usage, and in the caracterization and the generalization of algorithmic properties of quality measures.
The "engineering for decision support" axis contains tools (in every sens) which facilitate the decision support process.
It is currently composed of 2 themes : the software platforms and model driven engineering for decision. The platforms accumulate the software implementations of the theoretical and algorithmic solutions proposed by the team, whereas the model driven engineering for decision handles the qualitative and quantitative complexity of the input data for the decision process.