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Modelling Word Activation in Semantic Networks: Three Scaled Entanglement Models Compared

  • David Galea
  • Peter Bruza
  • Kirsty Kitto
  • Douglas Nelson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7620)

Abstract

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being overestimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • David Galea
    • 1
  • Peter Bruza
    • 1
  • Kirsty Kitto
    • 1
  • Douglas Nelson
    • 2
  1. 1.Queensland University of TechnologyBrisbaneAustralia
  2. 2.University of South FloridaTampaUSA

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