首页> 外文会议>AI 2006: Advances in Artificial Intelligence; Lecture Notes in Artificial Intelligence; 4304 >Customer Online Shopping Behaviours Analysis Using Bayesian Networks
【24h】

Customer Online Shopping Behaviours Analysis Using Bayesian Networks

机译:使用贝叶斯网络的客户在线购物行为分析

获取原文
获取原文并翻译 | 示例

摘要

This study applies Bayesian network technique to analyse the relationships among customer online shopping behaviours and customer requirements. This study first proposes an initial behaviour-requirement relationship model as domain knowledge. Through conducting a survey customer data is collected as evidences for inference of the relationships among the factors described in the model. After creating a graphical structure, this study calculates conditional probability distribution among these factors, and then conducts inference by using the Junction-tree algorithm. A set of useful findings has been obtained for customer online shopping behaviours and their requirements with motivations. These findings have potential to help businesses adopting more suitable online system development.
机译:本研究运用贝叶斯网络技术分析了顾客在线购物行为与顾客需求之间的关系。这项研究首先提出了一个初始的行为-需求关系模型作为领域知识。通过进行调查,收集了客户数据作为推断模型中描述的因素之间关系的证据。创建图形结构后,本研究计算这些因素之间的条件概率分布,然后使用Junction-tree算法进行推理。对于客户在线购物行为及其动机的要求,已经获得了一系列有用的发现。这些发现有可能帮助企业采用更适合的在线系统开发。

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