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dc.contributorAlatrista Salas, Hugo
dc.creatorAlvarez Mouravskaia, Kevin
dc.date.accessioned2020-06-26T16:53:00Z
dc.date.accessioned2020-06-28T05:05:58Z
dc.date.available2020-06-26T16:53:00Z
dc.date.available2020-06-28T05:05:58Z
dc.date.created2020-06-26T16:53:00Z
dc.date.issued2020-06-26
dc.identifier.urihttp://hdl.handle.net/20.500.12404/16531
dc.description.abstractMetaphors are an important literary figure that is found in books or and daily use. Nowadays it is an essential task for Natural Language Processing (NLP), but the dependence of the context and the lack corpus in other languages make it a bottleneck for some tasks such as translation or interpretation of texts. We present a classification model using recurrent neural networks for metaphor identification in Spanish sentences. We tested our model and his variants on a new corpus in Spanish and compared it with the current baseline using an English corpus. Our best model reports an F-score of 52.5% for Spanish and 60.4% for English.
dc.languagespa
dc.publisherPontificia Universidad Católica del Perú
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourcePontificia Universidad Católica del Perú
dc.sourceRepositorio de Tesis - PUCP
dc.subjectLingüística computacional
dc.subjectRedes neuronales
dc.subjectLenguaje natural--Procesamiento (Ciencia de la computación)
dc.titleMetaphor identification for Spanish sentences using recurrent neural networks
dc.typeinfo:eu-repo/semantics/masterThesis
dc.type.otherTesis de maestría


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