Determining the Optimal Environmental Information for Training Computational Models of Lexical Semantics and Lexical Organization.

Experiential theories of cognition propose that the external environment shapes cognitive processing, shifting emphasis from internal mechanisms to the learning of environmental structure. Computational modelling, particularly distributional models of lexical semantics (e.g., Landauer & Dumais, 1997...

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Published in:Canadian Journal of Experimental Psychology / Revue Canadienne de Psychologie Expérimentale Vol. 78; no. 3; pp. 163 - 174
Main Author: Johns, Brendan T.
Format: Article
Published: Canadian Psychological Association Sep2024
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Sep2024
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      pub: Canadian Psychological Association
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        atl: Determining the Optimal Environmental Information for Training Computational Models of Lexical Semantics and Lexical Organization.
      aug:
        au: Johns, Brendan T.
        affil: Department of Psychology, McGill University
      su:
        Computer simulation
        Ecology
        Information science
        Semantics
        Vocabulary
        Cognition
        Experiential learning
        Medical informatics
        Data mining
        Phonological awareness
        Data analytics
        Natural language processing
        Descriptive statistics
        Mathematical models
        Machine learning
        Theory
        Learning strategies
        Comparative studies
      sug:
        subj:
          Computer simulation
          Ecology
          Information science
          Semantics
          Vocabulary
          Cognition
          Experiential learning
          Medical informatics
          Data mining
          Phonological awareness
          Data analytics
          Natural language processing
          Descriptive statistics
          Mathematical models
          Machine learning
          Theory
          Learning strategies
          Comparative studies
      keyword:
        apprentissage automatique
        big data
        computational modeling
        lexical organization
        lexical semantics
        mégadonnées
        machine learning
        modélisation computationnelle
        organisation lexicale
        sémantique lexicale
        apprentissage automatique
        mégadonnées
        modélisation computationnelle
        organisation lexicale
        sémantique lexicale
        apprentissage automatique
        big data
        computational modeling
        lexical organization
        lexical semantics
        mégadonnées
        machine learning
        modélisation computationnelle
        organisation lexicale
        sémantique lexicale
        apprentissage automatique
        mégadonnées
        modélisation computationnelle
        organisation lexicale
        sémantique lexicale
      ab: Experiential theories of cognition propose that the external environment shapes cognitive processing, shifting emphasis from internal mechanisms to the learning of environmental structure. Computational modelling, particularly distributional models of lexical semantics (e.g., Landauer & Dumais, 1997) and models of lexical organization (e.g., Johns, 2021a), exemplifies this, highlights the influence of language experience on cognitive representations. While these models have been successful, comparatively less attention has been paid to the training materials used to train these models. Recent research has explored the role of social/communicatively oriented training materials on models of lexical semantics and organization (Johns, 2021a, 2021b, 2023, 2024), introducing discourse- and user-centred text training materials. However, determining the optimal training materials for these two model types remains an open question. This article addresses this problem by using experiential optimization (Johns, Jones, & Mewhort, 2019), which selects the materials that maximize model performance. This study will use experiential optimization to compare user-based and discourse-based corpora in optimizing models of lexical organization and semantics, offering insight into pathways towards integrating cognitive models in these areas.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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