| 一种适用于中小数据集的关联规则挖掘算法 |
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| 引用本文： | 林克明,陈淑珍. 一种适用于中小数据集的关联规则挖掘算法[J]. 计算机与数字工程, 2006, 34(11): 31-34 |
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| 作者姓名： | 林克明 陈淑珍 |
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| 作者单位： | 三明学院计算机科学系,三明,365004 |
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| 摘 要： | 探讨了Apriori算法的改进问题，提出了一种适用于中小数据集的关联规则挖掘算法。该算法主要特点是简单、清晰、高效。一方面充分使用了内存的高效存贮，另一方面使用了位运算快速进行计数，同时简化了Apriori算法中频繁项集的计算，大大的减少了中间变量及其存贮的时间和空间，提高了关联规则挖掘的速度和效率。
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| 关 键 词： | 数据挖掘 关联规则 Apriori算法 频繁项集 |
| 修稿时间： | 2006-01-05 |
A Data Mining Algorithm of Association Rules Can Be Applied to Medium or Small Datasets |
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| Lin Keming,Chen Shuzhen. A Data Mining Algorithm of Association Rules Can Be Applied to Medium or Small Datasets[J]. Computer and Digital Engineering, 2006, 34(11): 31-34 |
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| Authors: | Lin Keming Chen Shuzhen |
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| Abstract: | This paper studies an improved algorithm of Apriori,then a new algorithm of association rules mining that can be applied to medium or small datasets is presented.The main characteristics of the algorithm are simple,clear,efficient.Firstly,the new algorithm takes good use of the efficient storing of memory,on the other hand it uses bit operation to take count fast.At the same time the algorithm simplifies the calculation of frequent itemsets of Apriori algorithm,consumedly reduces the temporary variables and its time and space of storage,improves the speed and efficiency of association rule data mining. |
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| Keywords: | data mining association rules Apriori algorithm frequent itemsets |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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