河北移动经营分析系统家庭市场支撑子系统的设计与实现
|
摘要
随着3G业务的发展,三大运营商全业务竞争加剧,家庭市场竞争日趋激烈,对于家庭市场运营还处于起步阶段的中国移动而言,利用数据挖掘技术,建立家庭市场运营支撑平台迫在眉睫。
本文首先详细介绍数据挖掘的相关技术及数据挖掘方法论,针对河北移动迫切的家庭市场精细化管理需求,分析了家庭市场精细化管理中企业信息化存在的问题,提出了家庭市场支撑子系统建设思路,详细介绍了家庭客户识别模型的设计过程；接着介绍了家庭市场支撑子系统功能模块设计和接口模块以及数据库的设计过程；最后详细介绍了家庭客户识别模型在河北移动精细化营销体系中的应用。
作者参与了本系统立项分析、方案设计、开发实现、测试验收的全过程,负责系统设计和项目管理。
本文建立的家庭客户识别模型是数据挖掘应用在经营分析系统上的尝试,是对数据挖掘技术的进一步实践。通过本文的家庭客户识别的分析与研究,为电信企业进行家庭市场精细化营销工作提供了一定的保障。
With the development of 3G services and the fierce competition of China three full-service operators, the home market is still in the initial stages of operations of China Mobile. Therefore, it is urgent to establish a support platform for the home market through the applications of data mining techniques.
In this work, we first introduce data mining related technologies. Then, the environment of Hebei Mobile home is presented for urgent management of the market demand, including the detailed analysis of the home market in the enterprise information management problems. After that, we propose sub-market support family thinking of building, with details of family clients to identify the model design process, followed by the home market support subsystem module design, interface modules, and database design process. Finally, the customer identification of the family model in Hebei Mobile is refined in the marketing system application.
In this thesis, we describe our motivation, system design, key technologies, the experiments and tests. We experience the entire process of project analysis, design, developing, testing and acceptance, took charge of modeling, architecture design, and project management.
Modules in the thesis are a trial of data mining application in Heb-BASS system. The investigation on domestic customers' identification of telecom provides guarantee for precision marketing.
本文首先详细介绍数据挖掘的相关技术及数据挖掘方法论,针对河北移动迫切的家庭市场精细化管理需求,分析了家庭市场精细化管理中企业信息化存在的问题,提出了家庭市场支撑子系统建设思路,详细介绍了家庭客户识别模型的设计过程；接着介绍了家庭市场支撑子系统功能模块设计和接口模块以及数据库的设计过程；最后详细介绍了家庭客户识别模型在河北移动精细化营销体系中的应用。
作者参与了本系统立项分析、方案设计、开发实现、测试验收的全过程,负责系统设计和项目管理。
本文建立的家庭客户识别模型是数据挖掘应用在经营分析系统上的尝试,是对数据挖掘技术的进一步实践。通过本文的家庭客户识别的分析与研究,为电信企业进行家庭市场精细化营销工作提供了一定的保障。
With the development of 3G services and the fierce competition of China three full-service operators, the home market is still in the initial stages of operations of China Mobile. Therefore, it is urgent to establish a support platform for the home market through the applications of data mining techniques.
In this work, we first introduce data mining related technologies. Then, the environment of Hebei Mobile home is presented for urgent management of the market demand, including the detailed analysis of the home market in the enterprise information management problems. After that, we propose sub-market support family thinking of building, with details of family clients to identify the model design process, followed by the home market support subsystem module design, interface modules, and database design process. Finally, the customer identification of the family model in Hebei Mobile is refined in the marketing system application.
In this thesis, we describe our motivation, system design, key technologies, the experiments and tests. We experience the entire process of project analysis, design, developing, testing and acceptance, took charge of modeling, architecture design, and project management.
Modules in the thesis are a trial of data mining application in Heb-BASS system. The investigation on domestic customers' identification of telecom provides guarantee for precision marketing.
引文
[1]韩家威Data Mining:Concepts and Techniques机械工业出版社2004
[2]杨鸿宾客户分群技术在电信市场经营中的应用研究,科技咨询导报,2007年第09期
[3]吴川、关沉浮、柴天佑,数据仓库技术在移动通信业的应用,基础自动化,2002
[4]朱珠基于Hadoop的海量数据处理模型研究和应用[D]：北京邮电大学2008
[5]吴川、关沉浮、柴天佑数据仓库技术在移动通信业的应用基础自动化2002P40-42
[6]中国移动中国移动省级NG2-BASS技术规范总册V3.0.0 2010.8
[7]中国移动中国移动省级NG2-BASS业务规范V3.0.0 2010.8
[8]张济川logistic回归模型-方法与应用[M]高等教育出版社2001
[9]赵懿敏,精细化营销与客户分群,电信技术,2007年,第10期
[10]邵峰晶、丁忠清数据挖掘原理与算法[M]中国水利水电出版社2003
[11](美)派尔著,杨冬青等译《业务建模与数据挖掘》机械工业出版社2005-4-1
[2]杨鸿宾客户分群技术在电信市场经营中的应用研究,科技咨询导报,2007年第09期
[3]吴川、关沉浮、柴天佑,数据仓库技术在移动通信业的应用,基础自动化,2002
[4]朱珠基于Hadoop的海量数据处理模型研究和应用[D]：北京邮电大学2008
[5]吴川、关沉浮、柴天佑数据仓库技术在移动通信业的应用基础自动化2002P40-42
[6]中国移动中国移动省级NG2-BASS技术规范总册V3.0.0 2010.8
[7]中国移动中国移动省级NG2-BASS业务规范V3.0.0 2010.8
[8]张济川logistic回归模型-方法与应用[M]高等教育出版社2001
[9]赵懿敏,精细化营销与客户分群,电信技术,2007年,第10期
[10]邵峰晶、丁忠清数据挖掘原理与算法[M]中国水利水电出版社2003
[11](美)派尔著,杨冬青等译《业务建模与数据挖掘》机械工业出版社2005-4-1