目前人们经常使用决策树推理技术进行知识挖掘。
At present, people often use decision tree reasoning technique to mine knowledge.
在医院管理中如何把隐性知识挖掘出来，是一项很重要的任务。
In hospital management, how to dig up the tacit knowledge is a critical task.
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。
It is a problem power supply enterprise to solve that how to apply knowledge mining and knowledge management to electric power CRM.
离散类别确定后再应用粗糙集理论对其进行知识挖掘，可得到连续数据的本质特性。
Rough set theory is used to mine the knowledge and get the essence characteristics of the continuous data.
粗糙集和决策树是知识挖掘和学习的重要方法，通常用来分析数据和形成预测模型。
Rough Set and Decision Tree, usually used to analyze the data and the formation of predictive models, are important methods of knowledge discovery and learning.
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。
The content characteristics and outer characteristics representing information comprise the basis for the revelation of text knowledge correlation and knowledge mining.
知识管理模型基本上包括三个模块：目标体系，知识挖掘子系统和知识管理的支持系统。
The knowledge management model includes three parts: goal system, knowledge excavating subsystem and supporting subsystem of knowledge management.
应用于教育资源库建设的知识管理技术主要包括深度标引技术，知识挖掘技术和知识关联技术。
Knowledge management technology used in educational resource database includes deeper index technology, knowledge excavating technology and knowledge relating technology.
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。
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.
你可能会反对专业人士为了获取知识去挖掘，而不是金钱。
You might object that professionals excavate to acquire knowledge, not money.
数据挖掘是从大量的数据中萃取知识的一种科学。
Data mining is the science of extracting such knowledge from large amounts of data.
关于增加您的数据挖掘知识的其他方法，请参阅参考资料。
For additional ways to increase your knowledge about data mining, plan to check the Resources.
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。
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.
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。
Moreover, tools can partially automate asset harvesting - for instance, mining tools extracting architectural knowledge from project artifacts.
妈妈有许多知识和经验等待你去挖掘和尊敬。
Mom has lots of knowledge and lots experience for you to tap into and to honor.
这些仓库就像是杂乱的地下室，需要花费人力、资金和专门技能才能挖掘出业务知识。
These warehouses act like data silos and require effort, money, and expertise to mine for business knowledge.
在开发SwiftRiver的过程中，我们学习了很多关于挖掘实时内容的知识。
In developing SwiftRiver, we've learned a great deal about mining real-time content.
几年前，沼泽湿地带着她的专业知识回到索马里兰，她的使命是开始挖掘其文化底蕴。
Mire's professional journey brought her back to Somaliland a few years ago, where she embarked on a mission to unearth its cultural heritage.
数据挖掘(DM)是从数据库中发现知识。
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。
It is a process of spatial knowledge discovery and data mining. It sums up a modeling problem of the GIS-based reservoir evaluation.
数据挖掘，又称数据库中的知识发现，是指从大型数据库或数据仓库中提取隐含的、事先未知的、潜在有用的信息或模式。
Data Mining, also referred to as Knowledge Discovery from database, is to abstract the potential, unknown and useful information or pattern from the large database or data warehouse.
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。
In order to find the interested knowledge from datasets, it is required to use data mining which is useful in times of digital information.
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。
Date mining is a technology that it can find hidden knowledge in a large amount of data.
数据挖掘是从大量原始数据中抽取隐藏知识的过程。
Data Mining is the process of extracting hidden knowledge from large volumes of raw data.
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。
Knowledge is inexhaustible, inexhaustible. Only maximize the mining, it can experience the fun of learning.
IBM同时企盼类似的“云计算”能加速“大数据”时代的到来：即人们可以从海量的数字信息中挖掘出有用的知识。
It also anticipated that such cloud computing would accelerate the emergence of "big data" : huge piles of digital information that can be mined for valuable knowledge.
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。
The paper explores possible applications of Prior knowledge Support Vector Machine (P-SVM) based data mining algorithm in an automatic TCM syndrome classification system.
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。
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。
This paper expands the application area of OLAP, and it can also supply auxiliary support to potential knowledge Data Mining about basic research products.
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