This paper uses an optimization approach to address the problem of conceptual clustering. The aim of AGAPE, which is based on the tabu-search meta-heuristic using split, merge and ...
Abstract. This paper proposes a general framework for classifying data streams by exploiting incremental clustering in order to dynamically build and update an ensemble of incremen...
Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. V...
This work addresses the use of computational linguistic analysis techniques for conceptual graphs learning from unstructured texts. A technique including both content mining and i...
Our goal is to model the way people induce knowledge from rare and sparse data. This paper describes a theoretical framework for inducing knowledge from these incomplete data descr...
: In this paper we propose an application of data mining methods in the prediction of the availability and performance of Internet paths. We deploy a general decision-making method...