数据挖掘技术在网络游戏客户关系管理中的应用.docx
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数据挖掘技术在网络游戏客户关系管理中的应用
现今，数据挖掘技术已经在各个领域得以应用,并有了相当的发展。许多学者对数据挖掘的
研究及其在客户关系管理中的应用上获得了相当的突破,很多行业因此获益匪浅。
在我国，网络游戏作为一个新兴不久的行业，拥有着巨大的市场和庞大的潜力,但随之而来
的是愈发激烈的市场竞争，一些主流的游戏运营商已经把目光投向了在传统行业中取得了巨大
成功的客户关系管理体制。但是，不同于其他行业，网络游戏是建立在网络信息交流平台之上,
它所搜集到的客户数据更为庞大和繁杂，那么怎样从如此庞大的数据中找到有效资料呢？这就
需要应用到数据挖掘技术。
本文简要介绍了网络游戏客户关系管理的模式和内容以及几种主要的数据挖掘技术；着重
利用决策树玩家进行了分类、利用神经网络对玩家流失进行了分析、利用粗糙集对玩家信息进
行了挖掘。通过上述分析论证了数据挖掘技术在网络游戏客户关系管理中应用的可行性和有效
性.
关键词：网络游戏;客户关系管理；数据挖掘；应用
Abstract
At the present time， the application of the technique of data mining has
been developing in many kinds of elds. The experts has quite a number of
breakthrough in the data mining research and the customer relationship
management， which has brought great benets for many industries。
As a new-established industry, online games has the huge potential market
in China, but along with market competition, some of the online game operators
target the system of customer relationship management which has already been
much successful in the traditional industries。 Being di$erent from other
industries, online game is based on the communication platform of net
information, which can collect much more customer data。 How to nd the
e$ective information from such a giant database？ It needs the technique of data
mining.
This article will simply analyze the mode and the content about the
management of online game customer relationship， and introduce some major
kinds of DM techniques: classifying the players by decision tree, analyzing the
drain of players by neural net， and mining the player information by rough set.
It will demonstrate the feasibility and the e$ectivity of the application of DM
technique in the customer relationship management.
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