Structuring complex data using representativeness graphs

Abstract

This contribution addresses the problem of extracting some representative data from complex datasets and connecting them in a directed forest. First we define a degree of representativeness (DoR) based on the Borda aggregation procedure. Secondly we present a method to connect pairwise data using neighborhoods and the DoR as an objective function. We then present three case studies as a proof of concept: unsupervised grouping of binary images, analysis of co-authorships in a research team and structuration of a medical patient-oriented database for a case-based reasoning use.