Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/151246
Title: | Metaphoricity detection in adjective-noun pairs |
Other Titles: | Detección de metaforicidad en pares adjetivo-sustantivo |
Author: | Torres Rivera, Andrés ![]() Oliver, Antoni ![]() Coll-Florit, Marta ![]() |
Abstract: | In this paper we propose a neural network approach to detect the metaphoricity of Adjective-Noun pairs using pre-trained word embeddings and word similarity using dot product. We found that metaphorical word pairs tend to have a lower dot product score while literal pairs a higher score. On this basis, we compared seven optimizers and two activation functions, from which the best performing pairs obtained an accuracy score of 97.69% and 97.74%, which represents an improvement of 6% over other current approaches. Torres Rivera, A.[Andrés], Oliver, A. [Antoni]& Coll-Florit, M. [Marta]. (2020). Metaphoricity Detection in Adjective-Noun Pairs. Procesamiento del lenguaje natural, 64(null), 53-60. doi: 10.26342/2020-64-6 |
Keywords: | NLP metaphor Word Embeddings deep learning |
DOI: | https://doi.org/10.26342/2020-64-6 |
Document type: | info:eu-repo/semantics/article |
Version: | info:eu-repo/semantics/publishedVersion |
Issue Date: | Jan-2020 |
Publication license: | http://creativecommons.org/licenses/by/3.0/es/ ![]() |
Appears in Collections: | Articles Articles cientÍfics |
Files in This Item:
File | Description | Size | Format | |
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2020-MetaphocicityDection-Rivera_Oliver_CollFlorit.pdf | 1,13 MB | Adobe PDF | ![]() View/Open |
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