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감정 기반 키워드 속성값 산출에 따른 글꼴 추천 서비스

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DC FieldValueLanguage
dc.contributor.author지영서-
dc.contributor.author임순범-
dc.date.accessioned2023-11-08T08:47:42Z-
dc.date.available2023-11-08T08:47:42Z-
dc.date.issued2022-08-
dc.identifier.issn1229-7771-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/152539-
dc.description.abstractThe use of appropriate fonts is not only an aesthetic point of view, but also a factor influencing the reinforcement of meaning. However, it is a difficult process and wastes a lot of time for general users to choose a font that suits their needs and emotions. Therefore, in this study, keywords and fonts to be used in the experiment were selected for emotion-based font recommendation, and keyword values ​​for each font were calculated through an experiment to check the correlation between keywords and fonts. Using the experimental results, a prototype of a keyword-based font recommendation system was designed and the possibility of the system was tested. As a result of the usability evaluation of the font recommendation system prototype, it received a positive evaluation compared to the existing font search system, but the number of fonts was limited and users had difficulties in the process of associating keywords suitable for their desired situation. Therefore, we plan to expand the number of fonts and conduct follow-up research to automatically recommend fonts suitable for the user's situation without selecting keywords.-
dc.format.extent8-
dc.language한국어-
dc.language.isoKOR-
dc.publisher한국멀티미디어학회-
dc.title감정 기반 키워드 속성값 산출에 따른 글꼴 추천 서비스-
dc.title.alternativeFont Recommendation Service Based on Emotion Keyword Attribute Value Estimation-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.9717/kmms.2022.25.8.999-
dc.identifier.bibliographicCitation멀티미디어학회논문지, v.25, no.8, pp 999 - 1006-
dc.citation.title멀티미디어학회논문지-
dc.citation.volume25-
dc.citation.number8-
dc.citation.startPage999-
dc.citation.endPage1006-
dc.identifier.kciidART002873216-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorFont Emotion Analysis-
dc.subject.keywordAuthorFont Keyword-
dc.subject.keywordAuthorFont Recommendation-
dc.subject.keywordAuthorFont similarity-
dc.subject.keywordAuthorExperi- mental Interface-
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