Abstract. We propose a generic framework and methods for simplification of large networks. The methods can be used to improve the understandability of a given network, to complemen...
Classification is one of the most essential tasks in data mining. Unlike other methods, associative classification tries to find all the frequent patterns existing in the input...
Multicast-based inference has been proposed as a method of estimating average loss rates of internal network links, using end-to-end loss measurements of probes sent over a multic...
Graph-based similarity over WordNet has been previously shown to perform very well on word similarity. This paper presents a study of the performance of such a graph-based algorit...
Eneko Agirre, Montse Cuadros, German Rigau, Aitor ...
A new approach based on Estimation Distribution Algorithms for constrained multiobjective shape optimization is proposed in this article. Pareto dominance and feasibility rules ar...