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Metaphor Detection by Deep Learning Presented at FLAIRS-31, 2018

June 8th, 2018 margento
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Metaphor Detection by Deep Learning and the Place of Poetic Metaphor in Digital Humanities
Chris Tanasescu (Margento), Vaibhav Kesarwani, Diana Inkpen


The paper presents the work that has been done as part of the Graph Poem project in developing metaphor classifiers, now by deep learning methods (after previously having developed rule-based and machine learning algorithms), and a web-based metaphor detection tool. After reviewing the existing work on metaphor in natural language processing (NLP), digital humanities (DH), and artificial intelligence (AI), we present our own research and argue in favor of adopting data-intensive approaches, developing NLP classifiers, and applying graph theory (and particularly networks of networks) in computational literary or poetry analysis, while also highlighting the relevance of such work to DH, NLP, and AI in general.


poetry; metaphor; natural language processing; deep learning; digital humanities; graph theory applications; networks of networks


The whole paper (http://bit.ly/2xUR6On) is available here, http://bit.ly/2sRi9V7.


The entire Proceedings of the 31st Florida Artificial Intelligence Research Society Conference published by the Association for the Advancement of Artificial Intelligence are available here, http://www.aaai.org/Conferences/conferences.php

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