CAJ | 학술논문

不确定性数据的频繁项集挖掘的算法-U-apriori算法采用逐层迭代搜索方法，使用候选项集来找频繁项集。分析了U-apriori算法的流程和实现过程，并通过实验对比得出U-apriori算法花费较少时间和空间的优点，最后针对该算法的缺点提出了改进思路。结果表明：U-apriori算法是最佳概率频繁模式挖掘方法之一。
불학정성수거적빈번항집알굴적산법-U-apriori산법채용축층질대수색방법，사용후선항집래조빈번항집。분석료U-apriori산법적류정화실현과정，병통과실험대비득출U-apriori산법화비교소시간화공간적우점，최후침대해산법적결점제출료개진사로。결과표명：U-apriori산법시최가개솔빈번모식알굴방법지일。
Uncertainty data’ frequent item-sets excavation algorithm-U-apriori Algorithm adopts layer by layer and iteration method, which uses candidating item-sets to look for frequent item-sets. The article analyzes the process and realization of U-apriori Algorithm. By doing experiment and comparing, it conludes that U-apriori has the good point of less time and less space. The passage also points out some improving ways on the defects existed. The result is that U-apriori Algorithm is one of the best excavation ways of frequent patterns.