基于个人化的教学资源推荐系统的设计与评估技术

Teaching Resources Based on Personal Recommendation System Design and Evaluation

信息技术的发展使得数字资源爆发式增长,相关的推荐技术也显得越来越重要.基于个人化教学资源推荐系统的设计,是通过整合轻量目录访问协议(LDAP)与JAXB标准来提高推荐系统运行时对资料库剖析的效率,并通过分析使用者的搜索记录过滤出教学资源中的关键词及挖掘这些资源间的关联规则,进而使学习者高效地选择具有自适应性的教学资源.实验表明,智能型的学习推荐系统确实能提升学生的学习效率,同时让教学资源的内容更为丰富.

Development of information technology in recent years makes the explosive growth of digital resources,the relevant recommendation technology has become increasingly important.In this study,through the integration of LDAP and JAXB technologies to improve the recommendation system run-time analysis of the efficiency of the database,and by analyzing the user＇s search records in the key words to filter out curriculum resources and mining association rules among these resources,the platform will be different Integration of teaching resources on the same server,the experiments show that the system does improve the efficiency of student learning,while allowing richer materials.