This paper presents an improved multi-level association rule mining algorithm.
为此，提出一种改进的多层关联规则挖掘算法。
Aim To put forward association rule mining algorithm based on relation algebra theory.
目的提出基于关系代数理论的关联规则挖掘算法。
The date-set are managed equally and conformably in the traditional association rule mining algorithm.
传统的关联规则挖掘算法对更新的数据集按平等一致的方式加以处理。
Peculiarity association rule mining algorithm RSFPA based on FP-tree is presented by using FP-tree idea oriented association rule miming.
运用面向关联规则的FP树构造方法，提出了一种特异关联规则挖掘算法rsfpa。
Association rule mining algorithm is used for discovering association rules, and much research was carried out by many researchers and scholars.
关联规则挖掘算法用于发现关联规则，诸多的研究人员和学者对其进行了大量的研究。
The paper through the analysis of association rule mining algorithm, an improved association rule algorithm is applied to mining student achievement.
本文通过对关联规则挖掘算法的详细分析，应用了一种改进的关联规则算法对学生成绩进行挖掘。
Finally, the characteristics and connection strategies of generator are presented, and based on subsume index, a breadth-first algorithm for mining non-redundant association rule is proposed.
最后，讨论了生成子的性质及连接策略，并在包含索引的基础上，给出了一种宽度优先的无冗余关联规则挖掘算法。
The experimental results show that this new algorithm has proven its significant performance in the sparse multidimensional association rule mining.
实验结果表明，新算法在对具有稀疏特性的多维关联规则的挖掘中体现了良好的性能。
This paper introduces partition method in data cube with different confidence, expatiates on multidimensional association rule data mining algorithm based on data cube partition.
介绍了在数据立方体上对于不同可信度的数据进行分块的方法，阐述了基于数据立方体分块的多维关联规则挖掘的算法。
Aiming at a familiar and simple constraint that some items must or must not present in rules, a fast clipped-transaction-based constraint association-rule mining algorithm was put forward.
针对一类常见而简单的规则中有项或缺项的约束，提出了一种基于事务数据修剪的约束关联规则的快速挖掘算法。
This paper presents a new algorithm for distributed mining association rules with item constraints called DAMICFP, which is based on a new type algorithm for association rule mining, FP-growth.
在分布式环境中挖掘约束性关联规则是当前研究的热点问题之一。
With historical equipment database, weighted association rule algorithm is adopted to conduct data mining. By using weighted association rules, a model base is established.
采用加权关联规则算法对设备历史数据库进行挖掘，建立加权关联规则模式库。
With historical equipment database, weighted association rule algorithm is adopted to conduct data mining. By using weighted association rules, a model base is established.
采用加权关联规则算法对设备历史数据库进行挖掘，建立加权关联规则模式库。
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