Comparativa de Aproximaciones a SVM Semisupervisado Multiclase para Clasificación de Páginas Web

In this paper we present a study for semi-supervised multiclass web page classification using SVM. We propose not only combining binary semi-supervised classifiers, but also multiclass supervised ones. Our experiments show great performance for the latter method, where ignoring unlabeled documents could be better for some cases, using only labeled documents for the learning task, directly based on supervised algorithms.