首页> 外文会议>2015 2nd World Symposium on Web Applications and Networking >Data mining techniques for E-business intelligence
【24h】

Data mining techniques for E-business intelligence

机译:电子商务智能的数据挖掘技术

获取原文
获取原文并翻译 | 示例

摘要

With the rapid development of E-business, enormous customer data is been accumulated daily in websites background databases. It is difficult to deal with by business systems due to the large number of online transactions Data mining techniques and tools can be used to analyze customers shopping behavior and consuming habits to better understand their needs and increase the profits of the organization. In this paper we have applied K-Means algorithm over sample data and determined the relationship between the types of customer's behavior over their age and gender.
机译:随着电子商务的飞速发展,每天在网站后台数据库中积累了大量的客户数据。由于存在大量的在线交易,因此业务系统很难处理数据挖掘技术和工具可用于分析客户的购物行为和消费习惯,以更好地了解他们的需求并增加组织的利润。在本文中,我们对样本数据应用了K-Means算法,并确定了客户行为类型随年龄和性别的关系。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号