摘要
企业在管理过程中产生了大量的数据,这些数据的背后隐藏着与企业密切相关的极其重要的知识。聚类、关联规则、序列模式、统计分析、特征规则等数据挖掘方法能从这些海量数据中发现有用的知识,使数据真正成为企业的财富,为企业的决策和发展服务。目前数据挖掘已被广泛应用于银行、电信等行业,用来对客户数据进行正确的分析,挖掘消费模式,预测客户未来的行为,针对客户的需求提供个性化的服务。
The enormous data, generated during management process of enterprise, together with very critical knowledge hidden therein, are closely connected to the enterprise. Data mining methods such as clustering, association rules, sequential pattern, statistics analysis, characteristics rules, etc. can be used to find out useful knowledge, enabling such data to become the real fortune of enterprise and serve enterprise decision making and development. Currently, Data mining has been widely used in industries such as banking and telecommunication, for analyzing customer data accurately, mining consumption mode, predicting future behavior of customer and providing individuation service according to customer requirements.
出处
《商业研究》
CSSCI
北大核心
2008年第5期69-71,共3页
Commercial Research
基金
国家自然科学基金资助
项目编号:70601008
关键词
数据挖掘
聚类
关联规则
data mining
clustering
association rules
