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Symbol systems and perceptual representations

In Manuel de Vega, Arthur Glenberg & Arthur Graesser (eds.), Symbols and Embodiment: Debates on Meaning and Cognition. Oxford University Press. pp. 145--163 (2008)

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  1. Computational Exploration of Metaphor Comprehension Processes Using a Semantic Space Model.Akira Utsumi - 2011 - Cognitive Science 35 (2):251-296.
    Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization (...)
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  • An amodal shared resource model of language-mediated visual attention.Alastair C. Smith, Padraic Monaghan & Falk Huettig - 2013 - Frontiers in Psychology 4.
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  • Redundancy in Perceptual and Linguistic Experience: Comparing Feature-Based and Distributional Models of Semantic Representation.Brian Riordan & Michael N. Jones - 2011 - Topics in Cognitive Science 3 (2):303-345.
    Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We compare the representations (...)
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  • Computational Methods to Extract Meaning From Text and Advance Theories of Human Cognition.Danielle S. McNamara - 2011 - Topics in Cognitive Science 3 (1):3-17.
    Over the past two decades, researchers have made great advances in the area of computational methods for extracting meaning from text. This research has to a large extent been spurred by the development of latent semantic analysis (LSA), a method for extracting and representing the meaning of words using statistical computations applied to large corpora of text. Since the advent of LSA, researchers have developed and tested alternative statistical methods designed to detect and analyze meaning in text corpora. This research (...)
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