• 한국산업정보학회논문지
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• 제17권1호
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• pp.21-29
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• 2012

In this paper, we propose a new method to select colors representing the meaning of text contents based on the cognitive relation between words and colors, Our method is designed on the previous study revealing the existence of crucial words to estimate the colors associated with the meaning of text contents, Using the associative probability of each color with a given word and the strength of color association of the word, we estimate the probability of colors associated with a given text. The goal of this study is to propose a system to recommend the cognitively plausible colors for the meaning of the input text. To build a versatile and efficient database used by our system, two psychological experiments were conducted by using news site articles. In experiment 1, we collected 498 words which were chosen by the participants as having the strong association with color. Subsequently, we investigated which color was associated with each word in experiment 2. In addition to those data, we employed the estimated values of the strength of color association and the colors associated with the words included in a very large corpus of newspapers (approximately 130,000 words) based on the similarity between the words obtained by Latent Semantic Analysis (LSA). Therefore our method allows us to select colors for a large variety of words or sentences. Finally, we verified that our system cognitively succeeded in proposing the colors associated with the meaning of the input text, comparing the correct colors answered by participants with the estimated colors by our method. Our system is expected to be of use in various types of situations such as the data visualization, the information retrieval, the art or web pages design, and so on.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.342-343
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• 2021

색의 결합효과는 개인의 경험과 기호에 따라 커다란 영향을 받게 된다. 본 논문에서는 색이 가지는 결합적인 단어에 대하여 살펴보도록 한다. 그리고 색의 결합 언어 작용은 인간의 경험에 의한 상징을 동반한다. 이렇게 색의 결합효과에서 나오는 심리적 치료 효과도 살펴본다.

• 한국의류학회지
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• 제44권3호
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• pp.413-426
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• 2020

This study researches the association between associative vocabulary and fashion image language in order to extract ideas that can be used as basic data for design ideas. Classic - avant-garde imaged language were chosen as theme words and each 70 questionnaires per a final image word were used for analysis. We obtained the following results by researching keywords that explained classic image words through a word cloud technique. It was found to have high central representation in the order of suit, classical, basic, music, Chanel, black and traditional. The core key words explaining avant-garde image language were found to have a central representation in the order of : peculiar, huge, Comme des Garçons, artistic, creative, deconstruction and individuality. We extracted the necessary idea dimensions needed for design ideas through associative network graph analysis. In the case of classical image language, it was named as the Mannish Item, Music, Modern Color, and the Traditional Classicality dimensions. In the case of avant-garde image language, it was named as the Key Image, Artistic Aura, Key Design and Designers dimensions.