他说，如果你挖掘大学和研究中心所有的数据库，你会发现地球上最快乐的地方是…丹麦！
He says that if you mine all the databases of universities and research centers, you'll find that the happiest place on Earth is... Denmark!
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.
粗糙集理论被广泛应用于人工智能、模式识别、数据挖掘和知识发现等领域。
Rough sets theory was used widely to artificial intelligence, pattern recognition, data mining and knowledge discovery etc fields.
数据挖掘面对的任务是复杂的，通常包括分类、预测、关联规则发现和聚类分析等。
Data mining always faces complicated tasks that including classification, prediction, association rule discovering and clustering, etc.
提出了基于数据挖掘的网络入侵检测规则特征值自动发现算法和规则自动生成算法。
This thesis presents data mining aided signature automatic discovery algorithm for network based IDS and detection rule creation algorithm.
系统地概括了近年来天文学中数据挖掘和知识发现领域研究的进展及其热点，并阐述了其所面临的挑战。
Simultaneously, the research development, hot topic and challenges in the filed of data mining and knowledge discovery in database are summarized.
该文介绍了使用基于数据挖掘和知识发现的神经网络技术来解决库存问题的方法。
This paper introduces neural networks technology based on data mining and knowledge discovery for inventory problems.
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.
关联规则的发现是数据挖掘中最成功和最重要的一项任务，也是当今数据挖掘中一个非常活跃的研究领域。
At present, association rule, one of the most successful and crucial discoveries in data mining, has been an active research area.
摘要：粗糙集和灰色理论在数据挖掘领域各有优点，它们最终目标都是为了发现知识。
Absrtact: Rough sets and grey theory have advantages in the field of data mining, but their ultimate goal is to discover knowledge.
关联规则挖掘是数据挖掘和知识发现中一门重要技术，但基于支持度-置信度框架的关联规则挖掘存在一些问题。
Association rules mining is an important technique in data mining and KDD, but some problems exist in the association rules mining based on support and confidence.
其中主动空间数据挖掘技术主要体现在数据融合，数据挖掘和知识发现的过程中。
Active Spatial data mining technology is used in the processes of alarm data fusion, data mining and knowledge discovery.
大部分数据挖掘工具采用规则发现和决策树分类技术来发现数据模式和规则，其核心是归纳算法。
Most data mining tools use rule discovery and decision tree technology to extract data patterns and rules; its core is the inductive algorithm.
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.
网格为分布式数据挖掘和知识发现提供了有效的计算支持。
The grid plays an important role in providing a computational support for distributed data mining and knowledge discovery.
针对云理论在空间数据挖掘和知识发现中的应用，提出了基于半云和梯形云的空间距离概念的划分方法。
This thesis presents its application in spatial data mining and knowledge discovery, and focuses on the cloud models and their algorithms.
用于知识发现的大部分数据挖掘工具均采用规则发现和决策树分类技术来发现数据模式和规则。
Most data mining tools for knowledge discovery generally use rule discovery and decision tree technology to extract data patterns and rules.
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.
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.
最后从技术和应用的角度探讨了CRM中数据挖掘的应用，通过实证分析，发现和解决实际应用中的具体问题。
At last, the author discusses the application of data mining in CRM from technology and application and solves practicalities through demonstration analyses.
随着数据挖掘技术的出现，使人们能够从历史数据中去发现访客的行为规律，为访客提供智能化和个性化的服务。
With data mining technology, people can from the historical data to find the behaviour of visitors, and provide intelligent and personalized service to visitors.
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).
关联挖掘是数据挖掘中的一个重要问题，是发现和分析不同数据项之间的关联性的过程。
Association rules mining is a key issue in data mining. It discovers and analyses the associations among different sets of data items.
铜矿专家系统中知识库和规则库的保存和管理使用了数据库开发技术，采用数据挖掘作为知识发现的新手段。
The database development skills were applied to store and manage the knowledge and the rules while the knowledge founding adopted data mining technology.
数据挖掘技术能从大量数据中挖掘和发现有价值和隐含的知识，因而得到广泛的研究和应用。
Data mining technique can mine and discover valuable and hidden knowledge from databases, so it has been widely studied and applied.
采用基于专家库逻辑推理的试验数据知识提取方法来发现和挖掘试验数据。
The method of expert database logic inference for test data knowledge extracting is used to discover and explore test data.
采用基于专家库逻辑推理的试验数据知识提取方法来发现和挖掘试验数据。
The method of expert database logic inference for test data knowledge extracting is used to discover and explore test data.
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