| 一种基于MapReduce的Apriori改进算法研究 |
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| 引用本文： | 张艺雪,黄毅杰.一种基于MapReduce的Apriori改进算法研究[J].兰州工业高等专科学校学报,2014(6):13-16. |
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| 作者姓名： | 张艺雪 黄毅杰 |
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| 作者单位： | 1. 漳州卫生职业学院信息技术部,福建漳州,363000
2. 漳州职业技术学院计算机工程系,福建漳州,363000 |
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| 摘 要： | 提出了一种基于MapReduce模型,利用向量矩阵和Apriori算法实现关联规则数据挖掘的新算法.算法利用MapReduce模型处理向量矩阵,结合Apriori算法思想,产生局部频繁项集,通过合并处理得到全局频繁项集.实验证明算法能提高关联规则挖掘的效率.
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| 关 键 词： | 数据挖掘 关联规则 Hadoop Apriori MapReduce |
An Improved Apriori Algorithm Based on MapReduce |
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| ZHANG Yi-xue,HUANG Yi-jie.An Improved Apriori Algorithm Based on MapReduce[J].Journal of Lanzhou Higher Polytechnical College,2014(6):13-16. |
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| Authors: | ZHANG Yi-xue HUANG Yi-jie |
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| Affiliation: | ZHANG Yi-xue, HUANG Yi-jie(1.Department of Information Technology, Zhangzhou Health Vocational College, Zhangzhou 363000, China; 2. Department of Computer Engineering, Zhangzhou Institute of Technology, Zhangzhou 363000, China) |
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| Abstract: | A model based on MapReduce is proposed, which can use the vector matrix and Apriori algorithm to realize the data mining of association rules. The algorithm combined with the Apriori algorithm produces local frequent item sets, which obtains the global frequent item sets by combining process. Experiment turns out that the algorithm is effective. |
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| Keywords: | data mining association rules Hadoop Apriori MapReduce |
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