JobSphere让政府就业平台更智能易用，支持多语言语音交互和精准推荐。
JobSphere: An AI-Powered Multilingual Career Copilot for Government Employment Platforms
- 用RAG架构+4比特量化，在普通显卡上运行，成本降89%
- 简历解析识技能，岗位推荐精度@10达68%，响应快至1.8秒
- 适合农村及低数字素养用户，提升政府求职服务可及性
政府就业网站用户常因导航复杂、语言选项少、缺乏个性化支持而难以使用。本文提出JobSphere，一个面向旁遮普邦政府就业平台PGRKAM的AI职业助手。该系统采用检索增强生成（RAG）架构，支持英语、印地语和旁遮普语，通过4比特量化技术，可在消费级GPU（如NVIDIA RTX 3050 4GB）上部署，相较云端系统成本降低89%。核心功能包括语音交互、自动化模拟测试、简历技能识别，以及基于嵌入的岗位推荐，其精度@10达到68%。评估显示，系统事实准确率达94%，平均响应时间1.8秒，可用性评分78.5/100，较基线平台提升50%。结果表明，JobSphere有效填补了旁遮普邦及印地语使用者在偏远地区的就业服务空白，同时保障了用户获取政府权威岗位信息的可信度。
原文摘要 · Abstract (English)
Users of government employment websites commonly face engagement and accessibility challenges linked to navigational complexity, a dearth of language options, and a lack of personalized support. This paper introduces JobSphere, an AI-powered career assistant that is redefining the employment platform in Punjab called PGRKAM. JobSphere employs Retrieval-Augmented Generation (RAG) architecture, and it is multilingual, available in English, Hindi and Punjabi. JobSphere technique uses 4-bit quantization, allowing the platform to deploy on consumer-grade GPUs (i.e., NVIDIA RTX 3050 4GB), making the implementation 89% cheaper than that of cloud-based systems. Key innovations include voice-enabled interaction with the assistant, automated mock tests, resume parsing with skills recognition, and embed-based job recommendation that achieves a precision@10 score of 68%. An evaluation of JobSphere's implementation reveals 94% factual accuracy, a median response time of 1.8 seconds, and a System Usability Scale score of 78.5/100, a 50% improvement compared to the baseline PGRKAM platform context. In conclusion, JobSphere effectively fills significant accessibility gaps for Punjab/Hindi-speaking users in rural locations, while also affirming the users access to trusted job content provided by government agencies.
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