Modeling word perception using the Elman network

Cheng Yuan Liou*, Jau Chi Huang, Wen Chie Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

129 Citations (Scopus)

Abstract

This paper presents an automatic acquisition process to acquire the semantic meaning for the words. This process obtains the representation vectors for stemmed words by iteratively improving the vectors, using a trained Elman network. Experiments performed on a corpus composed of Shakespeare's writings show its linguistic analysis and categorization abilities.

Original languageEnglish
Pages (from-to)3150-3157
Number of pages8
JournalNeurocomputing
Volume71
Issue number16-18
DOIs
Publication statusPublished - Oct 2008
Externally publishedYes

Keywords

  • Authorship
  • Categorization
  • Compositional representation
  • Content addressable memory
  • Elman network
  • Linguistic analysis
  • Personalized code
  • Polysemous word
  • Semantic search
  • Stylistic similarity
  • Word perception

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