KDD2010比赛中基于Mahout协同过滤算法的应用研究

由于在线教育的迅猛发展,个性化教育应运而生,怎样在网络教育当中存储的海量用户数据提取反映用户学习能力水平与有助于提高用户学习水平的有价值信息特别关键,为此商业推荐领域广泛应用协同过滤推荐算法,以便将个性化推荐提供给用户使用者.本文通过在KDD2010比赛当中过滤技术作用发挥,有效结合教育数据挖掘,借助Apache Mahout的Taste组件各种方法,仿真建模教育数据,根据实施的实验反馈取得良好预测效果.

Application Research of Mahout based collaborative filtering algorithm in KDD2010 game

with the rapid development of online education, individualized education came into being, how massive user data stored in the network education extracted user learning ability and help to improve the level of user learning valuable information is particularly critical, therefore the commercial recommended widely applied to the field of collaborative filtering algorithm, so as to provide users with personalized recommendation for users. This paper through the filtering technology role in the KDD2010 game play, the effective combination of education with the method of data mining, Apache Mahout various Taste components, modeling and Simulation of education data, according to the implementation of the feedback experiment achieved good prediction effect.