摘要
针对Lossy Counting算法,即一个基于计数的确定性方案,提出一种新的基于权重的流数据频繁项挖掘算法(Lossy Weight),扩展了流数据频繁项的作用域。Lossy Weight算法不仅可用于传统的基于计数的频繁项挖掘,还可以挖掘出在整个流数据中所占权重比重大于门槛值的数据。实验数据分析证明该方案是有效的。
Lossy counting algorithm is a program based on counting ncertainty. This paper proposed a new flow of data based on the weight frequent items mining algorithm. Expanded the scope of current frequent item of data. Lossy weight algorithm can be used in the traditional count-based mining frequent item,also excavated in the entire flow data is larger than the proportion of total weight threshold data,analysis of experimental data show that the program is effective.
出处
《微型机与应用》
2011年第2期106-108,共3页
Microcomputer & Its Applications
关键词
频繁项
数据挖掘
权值
frequent item
data mining
weight