基于数据挖掘的学习推荐系统的研究

Research of the learning recommendation system based on data mining

为了让学习者在学习过程中能够快速获得所需的知识和核心内容,首先给出一个采用xml格式的多层次知识库,并基于学习者的身份特征、学习行为和测试结果,利用改进的协同过滤算法和基于约束的推荐算法,发现学习者的潜在学习需求,完成知识推送和个性化学习定制。最后,对学习推荐系统进行了实现。所研制的系统满足了学习者获得所需知识和学习指导的需求,提高了学习者的学习效率。

In order to let learners obtain the necessary knowledge and core content quickly in a learning process, this paper presents an improved collaborative filtering algorithm and recommendation algorithm based on constraints to find learners’ potential learning needs, thus accomplishs knowledge push and personalized learning customization. The algorithms work on a multi-level knowledge base in xml format, identity characteristics of learners, learning behaviors and test results. The learning recommendation system has been achieved. With the help of this system, the learners can get the necessary knowledge as well as the learning guidance more efficiently.