一种海量数据挖掘的有效方法

An Availability Measure of Data Mining on Mass Data

对大型数据库中海量数据进行数据挖掘的方法进行研究,提出一种对海量数据进行数据挖掘的有效方法,该方法实现了如何采用粒子群优化算法对海量数据进行优化划分,并且采用改进的Apriori算法解决Apriori算法产生大量候选项集和多次扫描数据库的缺点。从而解决海量数据挖掘的时间和空间复杂度过高的难点。

Through researching the measure of datamining on mass data in large database,this paper proposed an availability measure of datamining on mass data,this measure have achieved how to adopt the particle swarm optimization algorithm to partition the mass data optimization,and adopt an improved Apriori algorithm which resolve the shortcomings of Apriori algorithm,including generating a large number of candidate itemsets and scanning the database many times,so the new algorithm improves the speed and efficiency of datamining on mass data.