Complex networks have received much attention in the last few years, and reveal global properties of interacting systems in domains like biology, social sciences and technology. O...
Finding clusters with widely differing sizes, shapes and densities in presence of noise and outliers is a challenging job. The DBSCAN is a versatile clustering algorithm that can f...
We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the origin...
Abstract. This paper describes our approach to the Person Name Disambiguation clustering task in the Third Web People Search Evaluation Campaign(WePS3). The method focuses on two a...
Motivated by the principle of agnostic learning, we present an extension of the model introduced by Balcan, Blum, and Gupta [3] on computing low-error clusterings. The extended mod...