This paper introduces DM (data mining) and its work procedure, and then points out some problems which should be considered in data mining, finally gives a concrete sample of data mining.
简要介绍了DM(数据挖掘)及其工作过程，并指出了数据挖掘过程中应注意的问题，最后给出了一个具体的数据挖掘的例子。
We put forward data mining procedure and its application field among CRM after describing the conception and frame of CRM and various data mining technologies.
在了解CRM的概念和框架、数据挖掘的各种技术后，还必须了解数据挖掘在CRM中的应用流程和应用的业务领域。
Mining land reclamation is a very complex systemic project. There are a lot of spatial data and spatial information during the whole procedure.
矿区土地复垦是一项极其综合的系统工程，其整个过程涉及到大量的空间数据与空间信息。
In the last, an application instance of association rules in power plant is presented depicting the procedure for implementing data mining and list result data of test.
最后是一个关联规则挖掘在电厂中的应用实例，描述了该数据挖掘实现的过程，最后给出试验数据结果。
Classification rules discovery is a procedure to construct a classifier through studying the training dataset. It is a very important part of data Mining and Knowledge discovery.
分类规则发现则是通过对训练样本数据集的学习构造分类规则的过程，是数据挖掘、知识发现的一个重要方面。
The Bayesian classification technology in Data mining was discussed, and the research was emphasized on the basic principle and the work procedure of the Naive Bayesian classification technology.
对数据挖掘中的贝叶斯分类技术进行了讨论，重点分析了朴素贝叶斯分类技术的基本原理和工作过程。
The paper studied the main theory and technology of data mining, the procedure of the data-mining and the based frame of a data-mining system.
研究了数据挖掘的主要理论和技术，数据挖掘过程和数据挖掘系统的原型框架。
Knowledge discovery is to abstract the previously unknown and potentially useful models from a large amount of data, and data mining is an important component in the procedure of knowledge discovery.
知识发现就是从大量的数据中抽取以前未知并具有潜在可用的模式，数据挖掘则是组成知识发现过程的重要环节。
The content and procedure of the application of data mining in CRM is discussed in this paper.
该文对数据挖掘技术在CRM中的应用内容和过程进行了研究。
The data mining theories consist of such sections as the concept, classification, technique, procedure and application of data mining.
主要是数据挖掘的概念，同时对数据挖掘进行了分类，简单的说明了数据挖掘技术、数据挖掘的过程及应用。
According to the data mining process, the procedure of data modeling, evaluation and data attribute reducing was deeply discussed.
遵循数据挖掘流程，详细介绍了数据属性的约简，模型建立以及模型评估的方法。
According to the data mining process, the procedure of data modeling, evaluation and data attribute reducing was deeply discussed.
遵循数据挖掘流程，详细介绍了数据属性的约简，模型建立以及模型评估的方法。
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