Intersecting Word Vectors to Take Figurative Language to New Heights

نویسندگان

  • Andrea Gagliano
  • Emily Paul
  • Kyle Booten
  • Marti A. Hearst
چکیده

This paper proposes a technique to create figurative relationships using Mikolov et al.’s word vectors. Drawing on existing work on figurative language, we start with a pair of words and use the intersection of word vector similarity sets to blend the distinct semantic spaces of the two words. We conduct preliminary quantitative and qualitative observations to compare the use of this novel intersection method with the standard word vector addition method for the purpose of supporting the generation of figurative language.

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تاریخ انتشار 2016