自动识别色觉障碍用户难以访问的网页，提升网页无障碍设计
A feasibility study on filtering low-accessibility web pages considering color vision deficiency
- 基于颜色可访问性构建预测模型，自动筛选低适配网页
- 在21个网页上测试，最高AUC达0.76，具备可行潜力
- 适合关注网页无障碍设计的开发者与设计师参考
近年来，通用设计的重要性日益凸显。色彩通用设计（CUD）是考虑色觉障碍（CVD）人群的一种通用设计形式。网页是提供各类信息与功能的重要媒介，因此通过融入CUD原则提升网页可访问性至关重要。本研究旨在帮助改善网页可访问性，提出一种自动过滤低可访问性网页的方法。为评估该方法的可行性，我们使用21个网页进行了实验，预测模型在识别低可访问性页面方面表现出合理准确率，最高AUC达到0.76。
原文摘要 · Abstract (English)
Recently, the importance of universal design has increased. Color universal design (CUD) is one type of universal design that takes people with color vision deficiency (CVD) into consideration. Websites are important media for providing various types of information and functions. Therefore, it is essential to enhance the accessibility of web pages by incorporating CUD principles. The goal of our study is to help improve the accessibility of web pages. Our approach is to automatically filter low-accessibility web pages. To evaluate the feasibility of this approach, we conducted an experiment using 21 web pages. The prediction model identified low-accessibility pages with reasonable accuracy, achieving a maximum AUC of 0.76.
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