Abstract:El acceso a la versión del editor puede requerir la suscripción del recurso Access to the published version may require subscription Abstract. In this paper we present a new model of semantic features that, unlike previously presented methods, does not rely on the presence of a labeled training data base, as the creation of the feature extraction function is done in an unsupervised manner. We test these features on an unsupervised classification (clustering) task, and show that they outperform primitive (low-l… Show more
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