摘要
文章分析网上每个学习者的个性化需求,提出基于Web挖掘技术的个性化系统框架。对Web使用挖掘关键算法进行了研究,提出基于双向约束的MFASM算法,通过编程验证了算法的优越性,实现了该算法在Web数据预处理和数据挖掘中的应用。通过试验结果表明,系统设计是可行的。
This paper analyzed single online learner＇s personal requirements. According to their requirements,a Personalized Recommendation System framework was proposed based on the technology of Web usage mining. The System provided 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 researched on a new algorithms：MFASM mining algorithm,and implemented the programming of the algorithms in the proceed of Web-based data preprocessing and mining.Finally,the result of the test indicated that the System designed in this paper was feasible.
出处
《铁路计算机应用》
2010年第4期52-54,共3页
Railway Computer Application
