基于朴素贝叶斯学习的电子商务网站客户兴趣分类的应用研究

随着电子商务的不断发展,用户的分析和分类对电子商务网站来说越来越重要。因此需要一个行之有效的方法来进行用户分类并对其进行个性化服务。在本文中,我们提出了一种可以根据用户的网页访问记录和网上交易记录来动态地对顾客进行分类的方法,主要是利用了改进型的朴素贝叶斯分类器,对用户在网站上的行为进行分类,从而得到用户的分类信息,其结果可以作为提供个性化服务的依据。文章通过实验证明了上述方法的有效性和正确性。

A Customer Classification Based on Naive Bayes Classifier

With the increasing interest and emphasis on customer demands in e-commerce, it is highly desired to extract customer features effectively and analyze customer orientations. This paper presents a new approach that employs a modified naive hayes classifier to group users dynamically based on their web access. Such a customer clustering meth- od should be performed prior to internet stores as the basis to provide individual service. The experimental results of this clustering technique show the efficiency of the algorithm.