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Author(s)

     D.J.K. Mewhort, M.N. Jones

Title

     Representing word meaning and order information in a composite holographic lexicon

Publication Name

     Psychological Review

Publication Type

     Journal
Publisher
     
Place
     
Editor(s)
     
Number
      1
School
     
Volume
      114
Chapter
     
Pages
      1-37
Other Publication Information
     
Publication Year
     2007
Abstract
     The authors present a computational model that builds a holographic lexicon representing both word meaning and word order from unsupervised experience with natural language. The model uses simple convolution and superposition mechanisms (cf. B. B. Murdock, 1982) to learn distributed holographic representations for words. The structure of the resulting lexicon can account for empirical data from classic experiments studying semantic typicality, categorization, priming, and semantic constraint in sentence completions. Furthermore, order information can be retrieved from the holographic representations, allowing the model to account for limited word transitions without the need for built-in transition rules. The model demonstrates that a broad range of psychological data can be accounted for directly from the structure of lexical representations learned in this way, without the need for complexity to be built into either the processing mechanisms or the representations. The holographic representations are an appropriate knowledge representation to be used by higher order models of language comprehension, relieving the complexity required at the higher level.
Keywords
     semantic memory, mental lexicon, latent semantic analysis, statistical learning, holographic
Website
     http://
Paper Status
     Published
DOI / Publication ID
     



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