data mining

data mining的基本解释

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数据挖掘

data mining所属的单词分类

Computer / 计算机 [234]

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与data mining相关的网络例句 [注：此内容来源于网络，仅供参考]

This paper summarizes the background and advantage of data mining, as well as the significance of data mining in the scientific research management of colleges and universities firstly, and then discusses the theory of data mining, association rules and the ideas of main algorithm, analyzes the classic Apriori algorithm and its existing problems as well as the basic solutions. After that, this paper proposes Multi-Dimensional Apriori algorithm which is designed specially for the mining of this paper; Then describes the structure of scientific research data mining system, defines subject-oriented mining tasks, including: mining the data about research projects, mining the data about papers, mining the data about academic writings. The association mining process is implemented by programing, a number of stimulating association rules are found, interpreted and analyzed.

本文首先综述了数据挖掘的研究背景、意义以及数据挖掘技术在高校科研管理中的应用现状和意义，然后在对数据挖掘相关理论、关联规则思想及主要算法进行讨论，分析经典Apriori算法及其存在的问题、基本解决方案后，提出了适合本文挖掘的多维Apriori算法的设计方案，并应用于本文挖掘中；接着论文介绍了科研数据的关联挖掘系统的结构，确定了面向主题的挖掘任务，包括：科研项目信息的挖掘、论文信息的挖掘、学术专著信息的挖掘等；设计了关联规则的实施过程，并通过程序编码得以实现，获得了多条有启发性的关联规则，并对其进行了解释与分析。

This text aims at the difference of several representative geology conditions in Yang Shui mining area, carried on the primary election to the mining method of Yang Shui mining area, introduced the new theories of numerical optimization choice of mining method that are fuzzy mathematics and artificial neural network etc, based on the existing mining methods that are feasible, adopt the fuzzy optimization choice principle of flexible neural networks, and synthesize several experts and fieldworkers' opinion, built up the related mathematical model and revised model, carried on processing of programming through computer, thus established each optimization mining project under several representative geology conditions in Yang Shui mining area, and carried on optimizing to the existent unreasonable parameter in mining project;have the great significance to aim at each kind of geology condition for each mining area to adjust the mining method in time in the course of mining, abandon chronically unreasonable mining method, full reclaim the mine's resource, lower the dilution rate、 loss rate of mineral mining, raise the production capacity of stope and economic benefit of mine.

本文针对洋水矿区几种典型地质条件差异，对洋水矿区采矿方法进行了初选，介绍了模糊数学和人工神经网络等采矿方法数值优选新理论，在现有可行性采矿方法的基础上，采用弹性神经网络模糊优选原理，并综合多位专家及现场工作者的意见，建立了相关的数学模型及修正模型，通过计算机进行编程处理，从而确立了洋水矿区几种典型地质条件下各自的最优采矿方案，并针对采矿方案中存在的不合理参数进行了优化，为各矿区针对各类地质条件在采矿过程中及时调整采矿方法，摈弃习惯性的不合理采矿方法，充分回收矿山资源、降低矿石开采的贫化率、损失率，提高采场生产能力以及矿山经济效益具有重大意义。

The data model is the data source for the integrated mining which is built by using Snow Flake Schema. The integrated mining model consists of local mining and global mining. That is to say, firstly, monitoring cell mining, point mining and monitoring data mining are fulfilled respectively, then global mining model is run to opimize the monitoring process. The paper brings forward how to build up these models and the framework, and what variables should be delivered.

首先，采用雪花结构建立了数据模型构架，为流程挖掘提供数据底层；然后建立了监测流程综合挖掘模型构架，给出了监测单元挖掘、监测点位挖掘和监测数据挖掘，以及综合挖掘的模型函数和参数，以局部优化和全局优化的思路实现了土壤环境监测全流程优化。

与data mining相关的网络解释 [注：此内容来源于网络，仅供参考]

Data Warehousing：数据仓库

11.9.8 数据仓库(Data Warehousing)和数据挖掘(Data Mining)数据挖掘(Data Mining)是对数据仓库中的数据进行进一步处理以得到更有用信息的过程. 数据挖掘工具被用来发现数据的联合和相关性来生成元数据(Metadata). 元数据可以单个信息子集中隐含的相关性.

KED7 Data Mining: Display Form：数据挖掘: 显示表格

KED6 Data Mining: Change Form 数据挖掘: 更改格式 | KED7 Data Mining: Display Form 数据挖掘: 显示表格 | KEDA Export Summarization Level 输出汇总层次

mining geologist：采矿地质师

mining geodesy 矿山测量学 | mining geologist 采矿地质师 | mining geology 矿井地质