| Apriori算法的进一步改进 |
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| 引用本文： | 王伟勤,郑燊海. Apriori算法的进一步改进[J]. 计算机与数字工程, 2009, 37(4): 20-23 |
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| 作者姓名： | 王伟勤 郑燊海 |
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| 作者单位： | 佛山科学技术学院信息与教育技术中心,佛山,528000;佛山科学技术学院信息与教育技术中心,佛山,528000 |
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| 摘 要： | 关联规则挖掘已取得了许多有效的算法，但当应用在海量事物数据库时，算法占用的内存空间仍有待降低。它给出了一种Apriori算法的进一步改进的算法。改进的算法合并了数据库D中的相同事物，降低了存储空间的占用。避免了Apriori算法中的模式匹配问题，从而提高了算法的效率。
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| 关 键 词： | 数据挖掘 关联规则 频繁项集 |
An Improvement for Apriori Algorithm |
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| Wang Weiqin,Zheng Shenhai. An Improvement for Apriori Algorithm[J]. Computer and Digital Engineering, 2009, 37(4): 20-23 |
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| Authors: | Wang Weiqin Zheng Shenhai |
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| Affiliation: | Center of Information and EducationTechnique School of Science and Engineering;Foshan University;Foshan 528000 |
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| Abstract: | Although many efficient algorithms have been proposed for the discovery of association rules,the EMS memory of algorithm is still reduced for great capacity for liquor magnanimity databases.An improvement Apriori algorithm has been introduced.The enhanced algorithm incorporates sameness transaction in database D,and at the same time reduces the used of EMS memory,avoids pattern matching to be used in the Apriori algorithm,thus improves efficiency of algorithm. |
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| Keywords: | data mining association rule frequent itemsets |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
