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

Andrew Gargett, John Barnden

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)103-114
Number of pages12
JournalWeb Intelligence and Agent Systems
Volume13
Issue number2
DOIs
Publication statusPublished - Jul 1 2015
Externally publishedYes

Keywords

  • Artificial intelligence
  • cognitive science
  • corpus linguistics
  • interactive system
  • natural language processing

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

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