DISTRIBUTED DATA MINING

被引:0
作者
Fiolet, Valerie [1 ]
Toursel, Bernard [2 ]
机构
[1] Univ Lille 1, Lab Informat Fondamentale Lille, UPRESA CNRS 8022, F-59655 Villeneuve Dascq, France
[2] Univ Mons, Serv Informat, B-7000 Mons, Belgium
来源
SCALABLE COMPUTING-PRACTICE AND EXPERIENCE | 2005年 / 6卷 / 01期
关键词
Data Mining; Association Rules; Distributed Processing; Heuristic;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Knowledge discovery in databases, also called Data Mining, is an increasing valuable engineering tool. The huge amount of data to process is more and more significant and requires parallel processing. Special interest is given to the search for association rules, and a distributed approach to the problem is considered. Such an approach requires that data be distributed to process the various parts independently. The research for association rules is generally based on a global criterion on the entire dataset. Existing algorithms employ a large number of communication actions which is unsuited to a distributed approach on a network of workstations (NOW). Therefore, heuristic approaches are sought for distributing the database in a coherent way so as to minimize the number of rules lost in the distributed computation.
引用
收藏
页码:99 / 109
页数:11
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