CAJ | 학술논문

针对传统关联规则算法存在较大规则冗余问题，提出基于最小单调约束闭包 Hadoop 并行化关联规则。首先，基于闭包算子约束规则等价关系集，给出了满足最小单调约束规则集，可有效地将约束规则集划分为不相交的等价规则类，降低冗余规则比率；其次针对大数据问题，采用 Hadoop 框架下 Mapreduce 并行计算模型，实现最小单调约束闭包关联规则的并行化计算，有效地提升算法对于大数据处理的可拓展性；最后通过在标准测试集上的实验对比，显示了所提算法的有效性。
침대전통관련규칙산법존재교대규칙용여문제，제출기우최소단조약속폐포 Hadoop 병행화관련규칙。수선，기우폐포산자약속규칙등개관계집，급출료만족최소단조약속규칙집，가유효지장약속규칙집화분위불상교적등개규칙류，강저용여규칙비솔；기차침대대수거문제，채용 Hadoop 광가하 Mapreduce 병행계산모형，실현최소단조약속폐포관련규칙적병행화계산，유효지제승산법대우대수거처리적가탁전성；최후통과재표준측시집상적실험대비，현시료소제산법적유효성。
The closure minimal single constraint based Hadoop paralle association rules algorithm for large data environment is de-signed for the problem of large redundant rules in traditional association rule algorithm.Firstly,the smallest single constraint rules set is given according to the equivalence relations with closure operator constraint rules.It could efficiently divide the con-straint rules into disjoint equivalence rule class,and reduce redundant rules ratio.Secondly,Hadoop MapReduce parallel compu-ting model is applied to achieve the smallest enclosing a single constraint association rules parallel computing in big data,which effectively improve the algorithm expandation for large data processing.Finally,the effectiveness of the proposed algorithm is demonstrated by comparing the experimental results on the standard test set.