数据挖掘在企业中的应用.pdf

中国科学技术信息研究所
硕士学位论文
数据挖掘在企业中的应用
姓名:杨雪艳
申请学位级别:硕士
专业:情报学
指导教师:梁战平
20040801
数据挖掘在企业中的应用
摘要
从年 KDD 一词出现在第十一届国际联合人工智能学术会议上以来
数据挖掘技术己成为业界人士的研究热点其发展非常迅速应用更加广泛
数据挖掘技术融合了数据库人工智能机器学习统计学等多个领域的理论
和技术它能从大量数据中提取隐含在其中的人们事先不知道的有用的信
息和知识从而指导企业经营运作本人根据移动通信运营商的具体需求运
用 SPSS 公司的数据挖掘软件 Clementine 对电信企业大客户流失主题实施数
据挖掘通过数据分析得到影响移动通信运营商大客户流失的主要因素为企
业运用数据挖掘工具进行具体案例分析提供借鉴本文首先分析了数据挖掘出
现的必然性介绍了数据挖掘的概念历史研究现状热点和前景并分析
比较了与其相关的两项重要技术数据仓库和联机分析处理然后论述了数据
挖掘的方法步骤和数据挖掘工具的评价方法列举了数据挖掘在某些行业中
的具体应用并分析了我国数据挖掘应用不足的原因提出在数据挖掘项目实
施过程中应注意的问题
关键字数据挖掘KDD 数据仓库联机分析处SPSS Clementine 流失
The Application of Data Mining in Enterprise
Abstract
Data Mining (DM) technology has e a highly attractive field puter
science since the term Knowledge Discovery in Database (KDD) first appeared in
the 11th International AI Academic Conference in 1989. DM has been developed
rapidly and applied widely. bines theories and technologies of many fields,
such as Database, Artificial Intelligence, Machine Learning, and Statistics. It is able
to abstract unpredicted but valuable knowledge from mass data to guide business
operations of enterprises. According to specific requirements of the Mobil
munications, the author applied Clementine of SPSS Inc., a DM
software, to analyze reasons of VIP customers churning. Moreover, the author
sumarized the essful experience of implementing DM software to analyze data in
enterprise. In the first part, the author analyzed why the DM appeared, and explained
its concept, history,current research,hot topics and outlook. Secondly, the author
described pared Data Warehouse and On-Line Analytical Processing which
are relevant to DM. In addition, the author explained methods and steps of DM in
detail, and methods for evaluation of some DM instrumental software. The author
enumerated some implementation cases in several fields, analyzed the cause why
DM is not popular in China, and pointed out some problems in implementing DM.