1) data mining view
数据挖掘视图
2) 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。
3) visual data mining
可视化数据挖掘
1.
the Application of Visual Data Mining Technology in the CRM of Insure Industry;
可视化数据挖掘技术在保险业CRM中的应用
2.
System-prototype of visual data mining based on OLAM;
一个基于OLAM的可视化数据挖掘系统原型
3.
The visual data mining technology is also mainly discussed according to classification of information, so reliability and high efficiency of data management and control under shar.
从港口物流信息的特点入手,提出基于控制理论的信息流程图,并围绕流程图中的信息输入与输出反馈两大部分提出港口物流信息平台建设的关键问题;结合港口物流信息平台实例,重点讨论共享架构的执行现状、意义和技术路线,并按照信息的类型,分别讨论针对空间信息和属性信息的可视化数据挖掘技术手段,从而保证信息平台在共享架构下实现可靠高效的数据管理与控制。
4) data mining visualization
数据挖掘可视化
1.
Application and research of data mining visualization techniques;
数据挖掘可视化技术应用与研究
5) video data mining
视频数据挖掘
1.
Research and Implementation of Video Data Mining Technique;
视频数据挖掘的方法研究及应用
2.
According to the characteristics of data mining and video sequences,concept of video data mining is defined in a narrow sense and a broad sense respectively.
目前视频数据挖掘概念、体系尚不明确,现有的一些分类方法不能突出数据挖掘关于"新颖性"这一特性。
6) visualization data mining
可视化数据挖掘
1.
By applying visualization data mining to the analysis of scientific text and reviewing the evolution new ideas and new methods of management science and engineering research this paper compared the distributions of research potential and research capability between of the domestic and of the abroad.
通过可视化数据挖掘方法的研究,使用数据挖掘和科技文本分析的方法,获取管理科学研究的新进展、新思想和新方法。
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。
参考词条