不确定数据的项集频繁概率近似算法

Approximation Algorithm for Probability of Frequent Item-sets in Uncertain Database

研究在不确定事务数据库中挖掘概率频繁项集的问题,探讨使用近似算法在不确定数据中的挖掘概率频繁项集的方法.首先分析不确定数据库与可能世界语言,然后介绍频繁概率的概念,最后分析如何使用近似算法挖掘不确定数据库中的概率频繁项集.从而降低运行时间,提高算法效率.

In order to reduce the running time and improve efficiency of algorithm, studying items of mining approximation algorithm for probabilistic frequent item-sets in uncertain transaction databases, this paper acquired how to use approximation algorithm to mine probabilistic frequent item-sets in uncertain base. Starting with analyzing connections between uncertain databases and possible worlds, the paper introduces what frequent item-sets is. At last, a method of mining probabilistic frequent item-sets by approximation algorithm in uncertain databases is concluded.