助手标题  
全文文献 工具书 数字 学术定义 翻译助手 学术趋势 更多
查询帮助
意见反馈
   数据挖掘应用 的翻译结果: 查询用时:0.951秒
图标索引 在分类学科中查询
所有学科
计算机软件及计算机应用
更多类别查询

图标索引 历史查询
 

数据挖掘应用
相关语句
  data mining application
     Data Mining Application Based on OLE DB FOR DM Specification
     基于OLE DB For DM规范的数据挖掘应用
短句来源
     Data mining application in CRM
     面向CRM的数据挖掘应用
短句来源
     Study of Data Mining Application Based on BP Algorithm
     基于BP算法的数据挖掘应用研究
短句来源
     Development of Data Mining Application with VB and ADO
     利用VB与ADO开发数据挖掘应用
短句来源
     In this paper, I have designed a data mining query language based on XML and DMPS(Data Mining Application Prototype System) based on the data mining query language, which explored the problem of data mining query language standardlization and reusage of data mining utilities.
     论文提出了一种基于XML的数据挖掘查询语言的设计,并提出了以数据挖掘查询语言为核心的面向数据挖掘应用的原型系统DMPS(Data Mining Application Prototype System),在数据挖掘查询语言标准化和数据挖掘功能可重用方面做出了有益的探索。
短句来源
更多       
  practicing data ming
     Study on Practicing Data Ming in Customers' Relation Management in Bank
     银行客户关系管理的数据挖掘应用研究
短句来源
  data mining applications
     Mining Model is expressed with forms by OLE DB for data mining , and a new SQL-like DDL leverages developers to build data mining applications using SQL Server 2000.
     OLE DB for Data Mining以表的形式表达数据挖掘模型对象,而且也提供一种类似SQL的DDL使开发者能更好地建立数据挖掘应用。 本文给出了一个关于运用SQL Server2000构建数据挖掘应用的实例。
     At the end it points out how to apply data mining applications in CRM.
     最后指出了如何在CRM中实施数据挖掘应用
短句来源
     The aim of DMPS is: to abstract the core part from data mining applications and put them into a reusable and extensible prototype system, and to help data mining developers build data mining application system rapidly by applying components and framework in DMPS.
     DMPS 系统的设计目标是,抽象出数据挖掘应用系统中的核心部分,把它们封装在一个可重用可扩展的原型系统里面,使得开发人员可以应用原型系统中的部件和框架,方便快捷地开发数据挖掘应用系统。
短句来源
     The aim of DMPS is: to abstract the core part from data mining applications and put them into a reusable and extensible prototype system, and to help data mining developers build data mining application systems rapidly by applying components and framework in DMPS.
     DMPS的设计目标是,抽象出数据挖掘应用系统中的核心部分,把它们封装在一个可重用可扩展的原型系统里面,使得开发人员可以应用原型系统中的部件和框架,方便快捷的开发数据挖掘应用系统。
短句来源
     Mining maximum frequent itemsets is a key problem in many data mining applications.
     挖掘最大频繁项目集是多种数据挖掘应用中的关键问题 .
短句来源
更多       
  “数据挖掘应用”译为未确定词的双语例句
     The Application of Data Mining Based on CRM
     面向CRM的数据挖掘应用
短句来源
     The paper introduces the application technology of OLAP data mining based on supply chains, and discusses working mode of OLAP data mining system.
     文中介绍了基于供应链数据仓库的OLAP数据挖掘应用技术,最后给出了应用实例,并讨论供应链数据仓库的OLAP数据挖掘系统的工作模式及其今后的研究方向。
短句来源
     Spatial Database Oriented Application Research on Spatial Data Mining
     面向空间数据库的空间数据挖掘应用研究
短句来源
     Study on the Application of Data Mining Based on IDS (Intrusion Detection System)
     基于入侵检测的数据挖掘应用研究
短句来源
     Study on the Application of Data Mining Based on Police Information
     基于公安信息的数据挖掘应用研究
短句来源
更多       
查询“数据挖掘应用”译词为用户自定义的双语例句

    我想查看译文中含有:的双语例句
例句
为了更好的帮助您理解掌握查询词或其译词在地道英语中的实际用法,我们为您准备了出自英文原文的大量英语例句,供您参考。
  data mining application
Data mining application to proteomic data from mass spectrometry has gained much interest in recent years.
      
Guidelines are provided for implementing parallel and distributed data mining on large data sets, and a proof-of-concept data mining application is analysed using a neural network.
      
Advanced Scout is a PC-based data mining application used by National Basketball Association (NBA)coaching staffs to discover interesting patterns in basketball game data.
      
Adaptable similarity queries based on quadratic form distance functions are widely popular in data mining application domains including multimedia, CAD, molecular biology or medical image databases.
      
Exploration of the Performance of a Data Mining Application via Hardware Based Monitoring
      
更多          
  data mining applications
Finally, the MCLP method was compared with a well-known artifical neural network algorithm to test for the relative potential of different data mining applications in HAD research.
      
More importantly, TCSOM is a one-pass algorithm, which is extremely suitable for data mining applications.
      
It is also noted that this novel methodology has general utility for rule-induction, and data mining applications.
      
Examples include algorithms that explicitly guard against privacy breaches through linear transformations, exploiting multiplicative and colored noise for preserving privacy in data mining applications.
      
Data distortion is a critical component to preserve privacy in security-related data mining applications, such as in data mining-based terrorist analysis systems.
      
更多          


In recent years, the state of data rich and knowledge poor has to the rapid development of data mining,and researches in many different fields have shown great interest about it. The application of data mining has also kept growing quickly including traditional expert system and the hottest internet services which need the techniques of data mining to adapt the explosion of databases.In this paper the author first introduce the basic concept and process of KDD/data mining,then the fundamental ideas and methods...

In recent years, the state of data rich and knowledge poor has to the rapid development of data mining,and researches in many different fields have shown great interest about it. The application of data mining has also kept growing quickly including traditional expert system and the hottest internet services which need the techniques of data mining to adapt the explosion of databases.In this paper the author first introduce the basic concept and process of KDD/data mining,then the fundamental ideas and methods of data mining are summarized. many application systems are also listed,and especially some Web-based mining systems are discussed in detail.

数据挖掘是当前数据库和信息决策领域的最前沿研究方向之一。首先介绍了数据挖掘的基本概念和处理过程 ,然后分别分析了数据挖掘所发现的主要知识类型和使用的技术方法 ,最后对基于 Web的几个数据挖掘应用系统进行了较为细致的剖析 ,并指出数据挖掘技术和搜索引擎技术的结合对网络信息的发现、搜集和管理、利用具有巨大的发展前景

Data mining, or knowledge discovery in databases (KDD), has been emerging as a new research field and a new technology for discovery of interesting, implicit, and previously unknown knowledge from large databases. This paper classifies data mining according to the kinds of technique methods. The application scope and characteristics of every method are discussed . At last, the prospects of data mining is elaborated as well.

数据挖掘是指从数据库中提取出隐含的、先前不知道的有用知识的过程。本文从数据挖掘和知识发现的概念出发 ,总结了数据挖掘常采用的技术方法 ,并从数据挖掘采用的技术方法的角度对数据挖掘进行分类 ,指出每种技术适合挖掘出哪些知识 ,比较每种技术的优缺点 ,同时还对几个数据挖掘的应用进行了阐述。

In this paper the architecture of data mining is outlined and the general methods and procedure of data mining engineering is presented. At last, the future application of data mining is introduced.

首先介绍了数据挖掘的体系结构 ,并在此基础上提出了数据挖掘工程的一般方法和步骤 ,最后介绍了数据挖掘的应用前景

 
<< 更多相关文摘    
图标索引 相关查询

 


 
CNKI小工具
在英文学术搜索中查有关数据挖掘应用的内容
在知识搜索中查有关数据挖掘应用的内容
在数字搜索中查有关数据挖掘应用的内容
在概念知识元中查有关数据挖掘应用的内容
在学术趋势中查有关数据挖掘应用的内容
 
 

CNKI主页设CNKI翻译助手为主页 | 收藏CNKI翻译助手 | 广告服务 | 英文学术搜索
版权图标  2008 CNKI-中国知网
京ICP证040431号 互联网出版许可证 新出网证(京)字008号
北京市公安局海淀分局 备案号:110 1081725
版权图标 2008中国知网(cnki) 中国学术期刊(光盘版)电子杂志社