1) Graph-based data mining
基于图的数据挖掘
2) trajectory-oriented data mining
基于轨迹的数据挖掘
3) web-based spatial data mining
基于Web的空间数据挖掘
4) a content-based data mining
基于内容的数据挖掘
1.
On this basis,a content-based data mining algorithms,it is a two-stage retrieval technology,coupled with rough sets,approximate matching(fuzzy set theory),K-means clustering methods,as well as user feedback mechanisms combining algorithms.
在此基础上提出了一种基于内容的数据挖掘算法,它是两阶段检索技术,再加上粗集,近似匹配(模糊集理论),K-means聚类等数据挖掘方法以及用户反馈机制等相结合的算法。
5) Ogenetic data mining
基因的数据挖掘
6) 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。
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