It is a problem power supply enterprise to solve that how to apply knowledge mining and knowledge management to electric power CRM.
把知识挖掘和知识管理运用到电力客户关系管理是供电企业亟需解决的问题。
The content characteristics and outer characteristics representing information comprise the basis for the revelation of text knowledge correlation and knowledge mining.
能够体现信息的内容特征和外表特征共同构成了文本知识关联揭示和知识挖掘的基础。
This project studied the key technologies for the management of XML documents, including the storage and query of XML documents, the semantics of XML documents, and the knowledge mining, etc.
本项目研究XML文档管理的若干关键技术，包括XML文档的存储与查询，XML数据的语义，针对XML数据的知识挖掘等。
For additional ways to increase your knowledge about data mining, plan to check the Resources.
关于增加您的数据挖掘知识的其他方法，请参阅参考资料。
Using these tools, and following some of the examples that have been given, you now have a good base level of knowledge so you can begin to work on data mining a website.
通过这些工具，结合本文提供的一些示例，现在您已经拥有了良好的知识基础，可以开始对某个网站进行数据挖掘了。
Moreover, tools can partially automate asset harvesting - for instance, mining tools extracting architectural knowledge from project artifacts.
除此之外，工具能够部分地自动化生成资产 ——比如，从项目工件中提取出架构知识的挖掘工具。
Traditional DM (data Mining), basically, is a data-analyzing tool for local data at present and only can produce few of generalized or understood knowledge from local datasets.
传统的数据挖掘基本上是一个本地的数据分析工具，仅能对本地数据集产生一定的理解性或概括性的知识。
Data Mining (DM) is the knowledge discovery from databases.
数据挖掘(DM)是从数据库中发现知识。
Knowledge is inexhaustible, inexhaustible. Only maximize the mining, it can experience the fun of learning.
知识是取之不尽，用之不竭的。只有最大限度地挖掘它，才能体会到学习的乐趣。
This paper expands the application area of OLAP, and it can also supply auxiliary support to potential knowledge Data Mining about basic research products.
本文拓展了OLAP技术的应用领域，为挖掘基础研究成果数据的潜在知识提供辅助支持。
In order to find the interested knowledge from datasets, it is required to use data mining which is useful in times of digital information.
为了从数据集中发现感兴趣的知识规则，须得利用好数据挖掘这一数字信息时代的利器。
This system adopts data mining technique to obtain useful information and knowledge from existing products database, knowledge storehouse and regulation storehouse to support conceptual design.
本系统采用数据挖掘技术从已有的产品数据库、知识库和规则库中获取有用信息和知识以支持产品概念设计。
Date mining is a technology that it can find hidden knowledge in a large amount of data.
数据挖掘技术是对大量数据进行分析，发现数据中隐藏知识的一种技术。
This system adopts data mining technique and obtains useful information and knowledge from existing products database, knowledge storehouse and regulation storehouse to support conceptual design.
采用数据挖掘技术从已有的产品的数据库、知识库、规则库中获取有用的信息和知识来有效地支持机械产品概念设计。
The paper explores possible applications of Prior knowledge Support Vector Machine (P-SVM) based data mining algorithm in an automatic TCM syndrome classification system.
目的：探讨带先验知识的支持向量机（P-SVM）数据挖掘算法在中医证候信息自动分类中的应用。
Data Mining, also known as knowledge Discovery in Database, distills knowledge from a mass of data.
数据挖掘就是从海量数据中提取知识，又被称为数据库中的知识发现。
In this paper, after making a analysis of the relate field of data mining and its basic questions, we provide a new method for knowledge discovery.
本文分析了数据挖掘技术的相关领域及其基本问题，为知识获取提供了一种新方法。
The comprehensive integrated DSS, which composed of data warehouse and OLAP, data mining, model base and knowledge base system, is a more sophisticated form of DSS.
将数据仓库、OLAP、数据挖掘、模型库、知识库系统结合起来形成的综合集成决策支持系统是更高形式的决策支持系统。
In the 21st century of the knowledge and economic time and facing with the fact of bursting data but poor knowledge, data mining has been put forward and applied in many fields of database management.
21世纪是知识经济的时代，面对数据爆炸而知识贫乏的现实，人们提出数据挖掘思想，并将其广泛应用到数据库管理的各个领域。
Machine learning and data mining techniques are applied to acquire knowledge and build a concept reasoning network based on semantic dictionary and large training set.
在已有的英语语义词典及大量训练集的基础上，应用机器学习、数据挖掘等技术进行知识获取并最终形成若干个概念推理网。
Data Mining is a domain which tries to extract knowledge and interesting information from very large-scale databases. This knowledge is hidden, unknown, but potentially useful.
数据挖掘是从大型数据库的数据中提取人们感兴趣的知识，这些知识是隐含的、事先未知的潜在有用信息。
An improved sequential pattern mining algorithm is proposed, which is based on sliding time window and can discover general earthquake sequences according to field knowledge.
结合地震预报的领域知识，面向具体的应用，提出了一种改进的基于滑动时间窗口的序贯模式挖掘算法，用来发现广义的地震序列。
The circumstances of rich data and lack of knowledge lead to the emergence of technology of data warehouse and data mining, and arouse the interests of people in various fields.
数据丰富而知识贫乏的状况导致了数据仓库和数据采掘技术的出现，引起了许多不同领域的人们的极大关注。
It is a process of spatial knowledge discovery and data mining. It sums up a modeling problem of the GIS-based reservoir evaluation.
其本身就是一个空间知识发现和挖掘的过程，实质可归结为基于GIS的油气储层评价建模问题。
Data mining and Knowledge discovery is the technology that can extraction of implicit, previously unknown, and potential useful information from data.
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。
Association rule mining which is a method of data mining reveals the latent information and knowledge.
作为一种数据挖掘的方法，关联规则揭示了数据中隐藏的信息和知识。
Association rule mining which is a method of data mining reveals the latent information and knowledge.
作为一种数据挖掘的方法，关联规则揭示了数据中隐藏的信息和知识。
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