SHICARO: Semi-supervised Hierarchical Clustering bAsed on Ranking features using Ontology
R. Yangui, A. Nabli & F. Gargouri · 2015
Motivated by these issues, the main trust of this paper is to propose a new semi-supervised algorithm (SHICARO) which follows to build a hierarchy of clusters with ranked features. It is a top-down iterative method to cluster knowledge contained in the ontology. Our method relies on a set of similarity measures that allow computing similarities between mixed semantically linked instances.