We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Craig Saunders, John Shawe-Taylor, Juho Rousu, S&a...
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Results of any clustering algorithm are highly sensitive to features that limit their generalization and hence provide a strong motivation to integrate shape information into the ...
Mohammed Ameer Ali, Gour C. Karmakar, Laurence S. ...
— The problem Min-Power k-Connectivity seeks a power assignment to the nodes in a given wireless ad hoc network such that the produced network topology is k-connected and the tot...
Xiaohua Jia, Dongsoo Kim, Sam Makki, Peng-Jun Wan,...
Abstract. In this paper we compare our selection based learning algorithm with the reinforcement learning algorithm in Web crawlers. The task of the crawlers is to find new inform...