为数字素养低的用户实时解释网页术语，提升理解效率。
A Contextual Help Browser Extension to Assist Digital Illiterate Internet Users
- 结合词典与大模型，悬停时自动弹出术语解释
- 92%用户理解力提升，搜索时间平均减少85%
- 适合普通网民、老年人及跨领域初学者使用
本文设计、实现并评估了一款浏览器扩展，可对网页中技术缩写和术语提供上下文帮助。该扩展融合人工精选的技术词典与OpenAI大语言模型（LLM），通过轻量级提示框实现实时定义。采用谷歌云自然语言处理（NLP）分类器与ChatGPT组成的双层AI管道，仅在识别页面为技术相关时激活提示逻辑，降低误触发率。一项包含25名参与者的混合方法研究显示，92%参与者报告对术语理解有所改善，96%确认比手动搜索节省时间，所有用户认为提示框不干扰浏览。词典定义平均响应时间为2135毫秒，远低于AI生成定义的16429毫秒和手动搜索的17200毫秒/术语。本工作展示了缓解数字鸿沟的实用实时方案，并为医疗、法律、金融等领域的上下文辅助提供了拓展路径。
原文摘要 · Abstract (English)
This paper describes the design, implementation, and evaluation of a browser extension that provides contextual help to users who hover over technological acronyms and abbreviations on web pages. The extension combines a curated technical dictionary with OpenAI's large language model (LLM) to deliver on-demand definitions through lightweight tooltip overlays. A dual-layer artificial intelligence (AI) pipeline, comprising Google Cloud's Natural Language Processing (NLP) taxonomy API and OpenAI's ChatGPT, classifies each visited page as technology-related before activating the tooltip logic, thereby reducing false-positive detections. A mixed-methods study with 25 participants evaluated the tool's effect on reading comprehension and information-retrieval time among users with low to intermediate digital literacy. Results show that 92% of participants reported improved understanding of technical terms, 96% confirmed time savings over manual web searches, and all participants found the tooltips non-disruptive. Dictionary-based definitions were appended in an average of 2135 ms, compared to 16429 ms for AI-generated definitions and a mean manual search time of 17200 ms per acronym. The work demonstrates a practical, real-time approach to bridging the digital literacy gap and points toward extending contextual help to other domains such as medicine, law, and finance.
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