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1)  graphical data mining
图数据挖掘
1.
In order to handle the subgraph isomorphism problem, the technique of substructure with its instances as a whole was adopted which had been proposed by a famous graphical data mining algorithm SUBDUE, and proposed two new conc.
将混杂进化算法引入图数据挖掘,定义了基于图的染色体表示与加边变异和减边变异算子。
2.
In order to overcome the limit that the greedy search,which is often used by some prevalent graphical data mining systems,may often end up by providing sub-optimal solutions,an evolutionary algorithm was imported to perform data mining on databases represented as graphs.
将进化算法引入图数据挖掘,以克服贪婪式查找易陷入局部极值的问题。
2)  image data mining
图像数据挖掘
1.
On this basis it discussed in detail the image data mining software prototype system.
本文针对图像数据挖掘技术,介绍了图像的挖掘过程、挖掘技术等问题,在此基础上详细讨论了对图像数据挖掘软件原型系统的研究。
2.
Applicating in image data mining,it can dig out the relevance of image data.
首先分析传统用在挖掘结构化数据关联规则的基本思想,然后分析图像数据的特征,找出图像数据与传统结构化数据的区别,最后结合图像数据的特性将传统的关联规则进行改进,并将它应用在图像数据挖掘中,挖掘出图像数据的相关性。
3)  data mining view
数据挖掘视图
4)  data mining
数据挖掘
1.
Improvement in second cooling control of slab continuous casting by data mining technology;
基于数据挖掘技术改进板坯连铸二冷控制
2.
Application of data mining in upgrading of CC process control system;
数据挖掘在连铸过程控制系统改造中的应用研究
3.
The application of data mining technology on flexible PVC formulation experimental research;
数据挖掘技术在软质聚氯乙烯配方实验研究中的应用
5)  date mining
数据挖掘
1.
In consideration of the demand by the mine date resource informationa lization and mine management rationalization,and based on a deep going analysis of the mine date and management information,combine with the characteristics of mine produce system,the mine date mining oriented mine management system structure is proposed and applied,make a resolution of the many mine but one mill run s problem.
针对当前矿山数据资源信息化及生产管理合理化的需求,在对矿山数据和管理信息等进行深入分析的基础上,根据矿山生产系统的特点,提出了面向矿山管理的生产数据挖掘的体系结构并加以应用,解决了多采一选采、选协调模型的建模难题。
2.
The decision support system (DSS) for greenhouse constructs of data warehouse and date mining technology.
温室决策支持系统是采用数据仓库技术和数据挖掘技术构建的。
6)  DM
数据挖掘
1.
Evaluation Criterion and Method of DM Algorithm;
数据挖掘算法的评价标准与方法
2.
DM in the Application of Knowledge Management for Tax Resources Monitoring;
数据挖掘在税源监控知识管理中的应用
3.
It adopts the KDD(Knowledge Discovery in Database) and DM(Data Mining) to mine rolling process database, A schedule model which combines knowledge model and mathematical model was used online to improve the existing schedule model.
该方法采用知识发现(KDD)和数据挖掘(DM)对轧制运行数据库进行挖掘,建立知识模型和数学模型相结合的负荷分配模型。
补充资料:数据挖掘研究院

数据挖掘研究院(china data mining research,cdmr)是一个专注于数据挖掘及其相关技术的讨论组织,参与者都是数据挖掘及其相关学科的爱好者。作为论坛的组织者我们也是数据挖掘的忠实爱好者,希望能够利用一些有限的资源为中国数据挖掘营造一个良好的发展环境。

说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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