Customer Identification and Recommendation System Research Based on Web Mining

摘要：

Electronic commerces prevalence and development brings a lot of information to customers, at the same time it causes customer information overload. The major challenge facing business website is determining how to assist customers to find the products they desire. This paper uses the web log explorer software to find paths used by customers to browse for products. Then corresponding product characteristics are combined using the association rule to classify customers. On the base of this, we try to classify new customers and dynamically recommend products to new customers in order to enhance their satisfaction. The objective is to accomplish customer and websites a win-win strategy. As an example, this paper analyzes three months(2008.6.1-2008. 8.31)of the encity website(www. encity.cn)log data.

关键词： web mining customer identification recommendation system

作者: Liu Weijiang Zhang Zhaohui Ceng Queling

作者单位: Business School, Jilin University, China

会议类型: 国际会议

会议名称: 第八届武汉电子商务国际会议(The Eighth Wuhan International Conference on E-Business)

会议地点: 武汉

会议语种:英文

页码: 156-161

在线出版日期: 2009-05-30（万方平台首次上网日期，不代表论文的发表时间）