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Detection and Aptness: A study in metaphor detection and aptness assessment through neural networks and distributional semantic spaces


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Title: Detection and Aptness: A study in metaphor detection and aptness assessment through neural networks and distributional semantic spaces
Authors: Bizzoni, Yuri
E-mail: yuri.bizzoni@gu.se
Issue Date: 31-Jan-2019
University: Göteborgs universitet. Humanistiska fakulteten
University of Gothenburg. Faculty of Arts
Institution: Department of Philosophy, Linguistics and Theory of Science ; Institutionen för filosofi, lingvistik och vetenskapsteori
Parts of work: Bizzoni, Yuri, Stergios Chatzikyriakidis, and Mehdi Ghanimifard. "" Deep" Learning: Detecting Metaphoricity in Adjective-Noun Pairs." Proceedings of the Workshop on Stylistic Variation. 2017. http://www.aclweb.org/anthology/W17-4906

Bizzoni, Yuri, MARCO SILVIO GIUSEPPE Senaldi, and Alessandro Lenci. "Finding the Neural Net: Deep-learning Idiom Type Identification from Distributional Vectors." (2018): 27-41. Submitted

Bizzoni, Yuri, and Mehdi Ghanimifard. "Bigrams and BiLSTMs Two neural networks for sequential metaphor detection." Proceedings of the Workshop on Figurative Language Processing. 2018. http://www.aclweb.org/anthology/W18-0911

Bizzoni, Yuri, and Shalom Lappin. "Deep Learning of Binary and Gradient Judgements for Semantic Paraphrase." IWCS 2017—12th International Conference on Computational Semantics—Short papers. 2017.http://www.aclweb.org/anthology/W17-6903

Bizzoni, Yuri, and Shalom Lappin. "Predicting Human Metaphor Paraphrase Judgments with Deep Neural Networks." Proceedings of the Workshop on Figurative Language Processing. 2018. http://www.aclweb.org/anthology/W18-0906

Bizzoni, Yuri, and Shalom Lappin. "The Effect of Context on Metaphor Paraphrase Aptness Judgments." arXiv preprint arXiv:1809.01060 (2018). https://arxiv.org/abs/1809.01060
Date of Defence: 2019-02-21
Disputation: Torsdag den 21 februari 2019, kl. 14.00, T302, Olof Wijksgatan 6
Degree: Doctor of Philosophy
Publication type: Doctoral thesis
Keywords: metaphor detection
deep neural network
distributional semantic spaces
metaphor aptness
Abstract: Metaphor is one of the most prominent, and most studied, figures of speech. While it is considered an element of great interest in several branches of linguistics, such as semantics, pragmatics and stylistics, its automatic processing remains an open challenge. First of all, the semantic complexity of the concept of metaphor itself creates a range of theoretical complications. Secondly, the practical lack of large scale resources for machine learning approaches forces researchers to work unde... more
ISBN: 978-91-7833-311-0
URI: http://hdl.handle.net/2077/58277
Appears in Collections:Doctoral Theses from University of Gothenburg / Doktorsavhandlingar från Göteborgs universitet
Doctoral Theses / Doktorsavhandlingar Institutionen för filosofi, lingvistik och vetenskapsteori

 

 

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