面向B2C平台的潜在客户识别研究
关键词 潜在客户 web数据挖掘 分类分析 决策树 神经网络
毕业论文外文摘要
Title The Research on Potential Customer Recognition based on B2C Platform
Abstract
The rapid development of e-commerce, promotes the changes of consumption consciousness and the enterprise management. Customer is the foundation of enterprise development, and the scale of existing customer is limited but potential customers are theoretically unlimited. The acquirement of potential customers is of great significance to the expansion of enterprises. This study aims to use web data mining to identify potential customer. In this paper, introduces the basic theory of data mining from the beginning. Then, the definition of B2C platform and analysis of its customer’s characteristics are given. According to these characteristics, a potential customer recognition method based on Web data mining is proposed which contains three steps. First of all, getting data. Next is data preprocessing which includes data cleaning, data transformation, user identification and session identification. Third step uses decision tree and Neural Networks to uncover hidden knowledge, judging by this, mining potential customer. Finally, empirical analysis. Result shows that the number of customer’s browsing page is the most important factors affecting user’s purchase intention while browse time and whether login or not is not significant to the result of classification.
Keywords potential customer web data mining classification Decision tree Neural network
目 次
一 绪论 1
1.1 研究背景 1
1.2 研究意义 2
1.3 研究内容与思路 2
1.4 论文结构 3
二 数据挖掘理论基础 4
2.1 数据挖掘定义及过程 4
2.2 数据挖掘功能 5
2.3 数据挖掘中分类方法 6
三 B2C电子商务的客户分类 8
3.1 B2C平台概述 8
3.2 B2C电子商务客户分类——web数据挖掘 9