基于Web挖掘的电子商务推荐系统中推荐方法研究

Study on the recommending methods used in e-commerce recommending system based on Web usage mining

以改进Apriori算法、K_means聚类算法和ARHP算法3种不同的Web挖掘技术为基础构造推荐算法,形成推荐集.仿真实验结果表明基于ARHP的推荐算法的覆盖率和准确度明显高于其他两种方法,可用于基于Web挖掘的电子商务推荐系统中.

In research about recommendation system in e-commerce based on web usage mining, three recommending methods based on improved technique about Apriori, K-means cluster way and ARPH technique are presented. In the testing we find the precision and coverage rates of the recommending method based on ARHP outperform the other two methods obviously, which can be utilized in the e-commerce recommendation system.