Metaphor Detection by Deep Learning and the Place of Poetic Metaphor in Digital Humanities

Tanasescu, Chris;Inkpen, Diana;Kesarwani, Vaibhav
(2018) Proceedings of the Florida Artificial Intelligence Research Society Conference The Thirty-First International Flairs Conference — published

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Authors
  • Tanasescu, ChrisUCLouvain
    Author
  • Inkpen, Diana
    Author
  • Kesarwani, Vaibhav
    Author
Abstract
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.
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Citations

Tanasescu, C., Inkpen, D., & Kesarwani, V. (2018). Metaphor Detection by Deep Learning and the Place of Poetic Metaphor in Digital Humanities. In FLAIRS (ed.), Proceedings of the Florida Artificial Intelligence Research Society Conference The Thirty-First International Flairs Conference. https://hdl.handle.net/2078.5/223573