An Improved Database Classification Algorithm for Multi-database Mining

被引：0
|
作者：
Li, Hong [1 ,2 ]
Hu, XueGang [3 ]
Zhang, YanMing [1 ,2 ]
机构：
[1] Hefei Univ, Dept Comp Sci & Technol, Hefei 230001, Peoples R China
[2] Hefei Univ, Key Lab Network & Intelligent Infomat Proc, Hefei, Peoples R China
[3] Hefei Univ Technol, Sch Comp & Informat, Hefei 230001, Peoples R China
来源：
FRONTIERS IN ALGORITHMICS, PROCEEDINGS | 2009年 / 5598卷
关键词：
Multi-database mining; Database Classification; Optimization algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Database classification is a data preprocessing technique for multi-database mining. To reduce search costs in the data from all databases, we need to identify those databases which are most likely relevant to a data mining application. Based on the related research, the algorithm GreedyClass and BestClassification [7] are improved in order to optimize the time complexity of algorithm and to obtain the best classification from in given databases. Theoretical analysis and experimental results show the efficiency of the proposed algorithm.
引用
收藏
页码：346 / +
页数：2
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