摘要
聚焦高职院校智慧图书馆的智能化升级,构建基于“微信小程序+轻量化后端”架构的AI伴学系统;通过整合职业导向知识图谱、自然语言处理(NLP及联邦学习算法),实现资源智能推荐、多模态交互与动态服务优化等核心功能;系统设计以降低技术门槛与提升服务精准性为目标,通过“教材-实训-行业标准”三位一体的资源聚合模式,解决传统图书馆资源配置与职业教育需求脱节的问题。
This study focuses on the intelligent upgrading of smart libraries in higher vocational colleges and constructs an AI companion learning system based on the architecture of"WeChat Mini-Program+Lightweight Backend."By integrating vocational-oriented knowledge graphs,natural language processing(NLP),and federated learning algorithms,the system achieves core functions such as intelligent resource recommendation,multimodal interaction,and dynamic service optimization.Designed to lower technical barriers and improve service precision,the system addresses the disconnection between traditional library resource allocation and vocational education needs through a trinity resource aggregation model of"textbooks-training-industry standards."Empirical results show that the system significantly enhances resource utilization and user interaction efficiency,providing a technically adaptable and cost-effective solution for digital transformation in higher vocational colleges.The study proposes paths to deepen the integration of AI technology with vocational education scenarios,offering theoretical and practical references for the construction of smart libraries in similar institutions.
作者
陈梅
CHEN Mei(Library,Wanbei Health Vocational College,Suzhou 234000,China)
出处
《宿州教育学院学报》
2025年第3期58-63,共6页
Journal of Suzhou Education Institute
关键词
高职院校
智慧图书馆
AI伴学系统
轻量化架构
资源整合
higher vocational colleges
smart library
AI learning companion system
lightweight architecture
resource aggregation
