2000 character limit reached
Using Recurrent Neural Network for Learning Expressive Ontologies (1607.04110v1)
Published 14 Jul 2016 in cs.CL and cs.AI
Abstract: Recently, Neural Networks have been proven extremely effective in many natural language processing tasks such as sentiment analysis, question answering, or machine translation. Aiming to exploit such advantages in the Ontology Learning process, in this technical report we present a detailed description of a Recurrent Neural Network based system to be used to pursue such goal.