Implementing and Evaluating a Font Recommendation System Through Emotion-Based Content-Font Mappingopen access
- Authors
- Lim, Soon-Bum; Ji, Young-Seo; Ahn, Byunghak; Park, Jae Hong; Song, Yoojeong
- Issue Date
- Feb-2024
- Publisher
- MDPI
- Keywords
- font recommendation system; content emotion analysis; emotion calculation models; usability evaluation; emotion-based font recommendation
- Citation
- APPLIED SCIENCES-BASEL, v.14, no.3
- Journal Title
- APPLIED SCIENCES-BASEL
- Volume
- 14
- Number
- 3
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/159770
- DOI
- 10.3390/app14031123
- ISSN
- 2076-3417
2076-3417
- Abstract
- 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.
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