Gen-meta: Generating metaphors using a combination of AI reasoning and corpus-based modeling of formulaic expressions

Andrew Gargett, John Barnden

    Research output: Contribution to conferencePaperpeer-review

    2 Citations (Scopus)

    Abstract

    Metaphor is important in all sorts of mundane discourse [19], [7]: ordinary conversation, news articles, popular novels, advertisements, etc. This presents a challenge to how Artificial Intelligence (AI) systems understand inter-human discourse (e.g. newspaper articles), or produce more natural-seeming language, as most AI research on metaphor has been about its understanding rather than its generation. To redress the balance towards generation of metaphor, we directly tackle the role of AI systems in communication, uniquely combining this with corpus-based results to guide output to more natural forms of expression.

    Original languageEnglish
    Pages103-108
    Number of pages6
    DOIs
    Publication statusPublished - 2013
    Event2013 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2013 - Taipei, Taiwan, Province of China
    Duration: Dec 6 2013Dec 8 2013

    Other

    Other2013 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2013
    Country/TerritoryTaiwan, Province of China
    CityTaipei
    Period12/6/1312/8/13

    Keywords

    • Artificial intelligence
    • Cognitive science
    • Interactive system
    • Natural language processing

    ASJC Scopus subject areas

    • Artificial Intelligence

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