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ID:33775442
大小:1.34 MB
页数:73页
时间:2019-03-01
《电子商务中顾客消费行为分析研究》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、学号:2008040169姓名:孙向群联系电话:13064055041Email:sunxqun@163.com院系:管理与经济学院专业:管理科学与工程单位代码:10445学号:2008040169分类号:TP392硕士学位论文论文题目:电子商务中顾客消费行为分析研究学科专业名称管理科学与工程申请人姓名孙向群指导教师马英红教授论文提交时间2010年12月7日独创声明本人声明所呈交的学位论文是本人在导师指导下进行的研究工作及取得的研究成果。据我所知,除了文中特别加以标注和致谢的地方外,论文中不包含其他人已经发表或撰写过的研究成果,也不包含为获得__
2、____________(注:如没有其他需要特别声明的,本栏可空)或其他教育机构的学位或证书使用过的材料。与我一同工作的同志对本研究所做的任何贡献均已在论文中作了明确的说明并表示谢意。学位论文作者签名:导师签字:学位论文版权使用授权书本学位论文作者完全了解学校有关保留、使用学位论文的规定,有权保留并向国家有关部门或机构送交论文的复印件和磁盘,允许论文被查阅和借阅。本人授权学校可以将学位论文的全部或部分内容编入有关数据库进行检索,可以采用影印、缩印或扫描等复制手段保存、汇编学位论文。(保密的学位论文在解密后适用本授权书)学位论文作者签名:导师签字:
3、签字日期:20年月日签字日期:20年月日I山东师范大学硕士学位论文目录摘要·····························································································································IAbstract·········································································································
4、···············III第一章绪论················································································································11.1课题研究背景与研究意义···············································································11.2国内外研究现状····································
5、···························································11.3本文研究的内容及主要研究方法···································································41.4论文的主要内容与章节安排···········································································4第二章电子商务背景知识·····························
6、···························································6第三章商业智能与数据挖掘····················································································63.1商业智能简介···································································································73.2数据挖掘概述·
7、··································································································83.2.1数据挖掘解决的商业问题·········································································83.2.2数据挖掘的任务···········································································
8、··············93.2.3数据挖掘项目的生命周期·····································
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