数据挖掘技术可以有效地从大量的客户数据中发现有用的信息和知识，进而可以有效提升客户关系管理的质量，达到提高银行竞争力的目的。
DM can find useful information and knowledge effectively from much customer 's data, and then promote effectively quality of CRM, it reaches the aim which can raise the bank competition.
粗糙集理论作为一种处理不完备信息的有力工具，已广泛应用于人工智能的许多领域，特别是数据挖掘和知识发现领域。
Rough set theory, a powerful tool to deal with incomplete information, has been widely used in the area of artificial intelligence, especially in data mining and knowledge discovery.
数据挖掘是数据库和信息决策领域的一个理论前沿，是知识发现的核心部分。
Data mining is a theory forward in the field of database and decision-making information, It is core of the knowledge discovery.
数据挖掘是帮助人们在海量数据中发现信息和知识的工具，广泛应用到各个领域，包括异常检测。
Data Mining Technology, a tool that can discover information and knowledge in large data set, is used many fields, including anomaly detection.
数据挖掘与知识发现技术可以从大量的数据中抽取出隐含的、以往未知而又非常有意义和有用的信息。
Data mining and Knowledge discovery is the technology that can extraction of implicit, previously unknown, and potential useful information from data.
并利用数据挖掘工具，发现隐藏在庞杂信息源中的知识和规律，为目标市场的分析与选择提供有价值的参考信息。
The knowledge and rule discovered by data mining tools are useful information for the analysis and selection of Objective market.
数据挖掘能从大量的日常积累的数据中发现潜在的、有价值的信息和知识，用于支持决策。
Mining data from a large number of day-to-day accumulation of data found potential, valuable information and knowledge, used to support decision-making.
因此，面对“数据丰富，但信息贫乏”的挑战，数据挖掘和知识发现技术应运而生。
So in facing of challenge of "Much data, but little information", there come Data Mining (DM) and Knowledge Discovery in Database (KDD).
因此，面对“数据丰富，但信息贫乏”的挑战，数据挖掘和知识发现技术应运而生。
So in facing of challenge of "Much data, but little information", there come Data Mining (DM) and Knowledge Discovery in Database (KDD).
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