Relational Data Mining Through Extraction of Representative Exemplars
With the growing interest on Network Analysis, Relational Data Mining is becoming an emphasized domain of Data Mining. This paper addresses the problem of extracting representative elements from a relational dataset. After defining the notion of degree of representativeness, computed using the Borda aggregation procedure, the authors present the extraction of exemplars which are the representative elements of the dataset. They use these concepts to build a network on the dataset. They expose the main properties of these notions and they propose two typical applications of their framework. The first application consists in resuming and structuring a set of binary images and the second in mining co-authoring relation in a research team.