Application of Web-based Data Mining in Personalized Online Learning System

摘要

Online learning has become an important part in the education system. However, the lack of personal service in a web environment is one of development bottlenecks of online learning system. First, this paper analyzes single online learner's personal requirements. According to their requirements, a personalized recommendation system framework is proposed based on the technology of web usage mining. The system provides individual recommendations in accordance with the analysis of single learner's study custom and interest, so the quality of service could be improved. Then, this paper researches on two key algorithms: maximum forward path (MFP) mining algorithm and association rules mining algorithm, and implements the programming of the two algorithms in the proceed of web-based data preprocessing and mining .Finally, the result of the test indicates that the system designed in this paper is feasible.