• Title/Summary/Keyword: Semantic Congruence

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The Changes of the Visual Dominance Effect due to Semantic Congruence of Visual and Auditory Information (시각과 청각 정보의 의미적 일치성에 따른 시각 우세성 효과의 변화)

  • Kim, Bo-Seong;Min, Yoon-Ki
    • Korean Journal of Cognitive Science
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    • v.20 no.2
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    • pp.109-124
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    • 2009
  • When visual and auditory information is presented simultaneously, we perceive visual information dominantly over auditory information. This effect is called the visual dominance effect. This study was to examine the influence of semantic congruence of visual and auditory information on the visual dominance effect. The semantic congruence of visual and auditory information was manipulated. The results showed that the visual dominance effect obtained in error rates was not modulated by semantic congruence, whereas the effect in RT was. It is suggested that this modulation of the influence of semantic congruence on the visual dominance effect would be due to the task type.

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A Recommender System Model Using a Neural Network Based on the Self-Product Image Congruence

  • Kang, Joo Hee;Lee, Yoon-Jung
    • Journal of the Korean Society of Clothing and Textiles
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    • v.44 no.3
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    • pp.556-571
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    • 2020
  • This study predicts consumer preference for social clothing at work, excluding uniforms using the self-product congruence theory that also establishes a model to predict the preference for recommended products that match the consumer's own image. A total of 490 Korean male office workers participated in this study. Participants' self-image and the product images of 20 apparel items were measured using nine adjective semantic scales (namely elegant, stable, sincere, refined, intense, luxury, bold, conspicuous, and polite). A model was then constructed to predict the consumer preferences using a neural network with Python and TensorFlow. The resulting Predict Preference Model using Product Image (PPMPI) was trained using product image and the preference of each product. Current research confirms that product preference can be predicted by the self-image instead of by entering the product image. The prediction accuracy rate of the PPMPI was over 80%. We used 490 items of test data consisting of self-images to predict the consumer preferences for using the PPMPI. The test of the PPMPI showed that the prediction rate differed depending on product attributes. The prediction rate of work apparel with normative images was over 70% and higher than for other forms of apparel.