Opposition theory and computational semiotics Cover Image

Opposition theory and computational semiotics
Opposition theory and computational semiotics

Author(s): Dan Assaf, Yochai Cohen, Marcel Danesi, Yair Neuman
Subject(s): Semiotics / Semiology, Computational linguistics
Published by: TARTU ÜLIKOOLI KIRJASTUS
Keywords: opposition theory; computational semiotics; metaphor identification

Summary/Abstract: Opposition theory suggests that binary oppositions (e.g., high vs. low) underlie basic cognitive and linguistic processes. However, opposition theory has never been implemented in a computational cognitive-semiotics model. In this paper, we present a simple model of metaphor identification that relies on opposition theory. An algorithm instantiating the model has been tested on a data set of 100 phrases comprising adjective noun pairs in which approximately a half represent metaphorical language-use (e.g., dark thoughts) and the rest literal language-use (e.g., dark hair). Th e algorithm achieved 89% accuracy in metaphor identification and illustrates the relevance of opposition theory for modelling metaphor processing.

  • Issue Year: 43/2015
  • Issue No: 2-3
  • Page Range: 159-172
  • Page Count: 14
  • Language: English