分析结果表明，利用规则兴趣度能够大大减小候选项目集的大小，有效提高频繁模式挖掘算法的效率。

The result indicates that we can remarkably decrease the candidate items and improve the efficiency of mining frequent pattern when using the interest measure.

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我们将它与另一种更新频繁项目集的算法FUP2比较，实验显示，UWEP2算法比FUP2算法生成的候选项目集要少，性能要高。

The experiments on synthetic data show that UWEP2 outperforms another algorithm FUP2 in terms of the generated candidates and efficiency.

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