Gen-Meta: Generating metaphors by combining AI and corpus-based modeling

Gargett, Andrew and Barnden, John (2015). Gen-Meta: Generating metaphors by combining AI and corpus-based modeling. Web Intelligence, 13(2) pp. 103–114.

DOI: https://doi.org/10.3233/WEB-150313

Abstract

Metaphor is important in all sorts of mundane discourse: ordinary conversation, news articles, popular novels, advertisements, etc. Issues of prime human interest – such as relationships, money, disease, states of mind, passage of time – are often most economically and understandably conveyed through metaphor. This ubiquity of metaphor presents a challenge to how Artificial Intelligence (AI) systems not only understand inter-human discourse (e.g. newspaper articles), but also produce more natural-seeming language; however, most AI research on metaphor has been about its understanding rather than its generation. To redress the balance, we directly tackle the role of AI systems in communication, uniquely combining this with corpus-based results to guide output toward more natural forms of expression.

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