Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mapping
Rapid digital content growth demands pivotal font selection for design and communication. Our study focuses on a font recommendation system that aligns fonts with content emotions. To achieve this, we define font-emotions and quantify them. Additionally, we leverage deep learning techniques for cont...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/3/1123 |
| _version_ | 1797319010841264128 |
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| author | Soon-Bum Lim Young-Seo Ji Byunghak Ahn Jae Hong Park Yoojeong Song |
| author_facet | Soon-Bum Lim Young-Seo Ji Byunghak Ahn Jae Hong Park Yoojeong Song |
| author_sort | Soon-Bum Lim |
| collection | DOAJ |
| description | Rapid digital content growth demands pivotal font selection for design and communication. Our study focuses on a font recommendation system that aligns fonts with content emotions. To achieve this, we define font-emotions and quantify them. Additionally, we leverage deep learning techniques for content analysis. Understanding common emotional perceptions, we aimed to align fonts with content emotions. After evaluating diverse mapping methods, we determined a correlation analysis-based model to be most effective. Implementing this model, we verified its utility through usability evaluations. Our proposed system not only assists users with limited design knowledge in receiving contextually fitting font suggestions but also extends its application across various digital content realms. |
| first_indexed | 2024-03-08T04:00:39Z |
| format | Article |
| id | doaj.art-8694b23b79bc4916b657ce361dc67a02 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-08T04:00:39Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-8694b23b79bc4916b657ce361dc67a022024-02-09T15:07:52ZengMDPI AGApplied Sciences2076-34172024-01-01143112310.3390/app14031123Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font MappingSoon-Bum Lim0Young-Seo Ji1Byunghak Ahn2Jae Hong Park3Yoojeong Song4Department of IT Engineering, Research Institute of ICT Convergence, Sookmyung Women’s University, Seoul 04310, Republic of KoreaDepartment of IT Engineering, Research Institute of ICT Convergence, Sookmyung Women’s University, Seoul 04310, Republic of KoreaVisual Communication Design, School of Design, Hongik University, Seoul 04066, Republic of KoreaDepartment of Visual Arts, Mokpo National University, Muan-gun 58554, Republic of KoreaSchool of Computer Science, Semyung University, Jecheon 27136, Republic of KoreaRapid digital content growth demands pivotal font selection for design and communication. Our study focuses on a font recommendation system that aligns fonts with content emotions. To achieve this, we define font-emotions and quantify them. Additionally, we leverage deep learning techniques for content analysis. Understanding common emotional perceptions, we aimed to align fonts with content emotions. After evaluating diverse mapping methods, we determined a correlation analysis-based model to be most effective. Implementing this model, we verified its utility through usability evaluations. Our proposed system not only assists users with limited design knowledge in receiving contextually fitting font suggestions but also extends its application across various digital content realms.https://www.mdpi.com/2076-3417/14/3/1123font recommendation systemcontent emotion analysisemotion calculation modelsusability evaluationemotion-based font recommendation |
| spellingShingle | Soon-Bum Lim Young-Seo Ji Byunghak Ahn Jae Hong Park Yoojeong Song Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mapping Applied Sciences font recommendation system content emotion analysis emotion calculation models usability evaluation emotion-based font recommendation |
| title | Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mapping |
| title_full | Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mapping |
| title_fullStr | Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mapping |
| title_full_unstemmed | Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mapping |
| title_short | Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mapping |
| title_sort | implementing and evaluating a font recommendation system through emotion based content font mapping |
| topic | font recommendation system content emotion analysis emotion calculation models usability evaluation emotion-based font recommendation |
| url | https://www.mdpi.com/2076-3417/14/3/1123 |
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