Expert Knowledge Integration in Data Mining

This is the earliest research axis, developed during the PhD (2003-2006, under the supervision of Martine Collard) and the years immediately after.

The central idea was to integrate expert domain knowledge into the data mining process, rather than treating pattern extraction as a purely statistical problem. This led to the ExCIS methodology (Extraction using a Conceptual Information System), building a domain-specific ontology to guide dataset preparation and results interpretation, and to the IMAK interestingness measure, which evaluates extracted patterns by taking expert knowledge into account rather than relying on objective statistical measures alone.

Applications included transcriptome analysis (the KTA and HASAR frameworks, with atherosclerosis risk factor analysis) and gene expression data mining.