| 基于频繁模式树的普遍化关联规则挖掘 |
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| 引用本文： | 李乃乾,沈钧毅,宋擒豹.基于频繁模式树的普遍化关联规则挖掘[J].小型微型计算机系统,2002,23(12):1469-1471. |
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| 作者姓名： | 李乃乾 沈钧毅 宋擒豹 |
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| 作者单位： | 西安交通大学,计算机软件研究所,陕西,西安,710049 |
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| 基金项目： | 国家自然科学基金(项目号60173058)资助. |
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| 摘 要： | 提出了基于频繁模式树的普遍化关联规则挖掘算法 MGAR- FP,充分利用频繁模式树的性质 ,避免大量候选模式的生成和频繁模式匹配 ,提高了挖掘的效率和速度 .实验表明 ,算法是有效的 ,比传统的普遍化关联规则挖掘算法Cum ulate快
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| 关 键 词： | 知识发现 数据挖掘 关联规则 概括 |
| 文章编号： | 1000-1220(2002)12-1469-03 |
Mining Generalized Association Rules Based on Frequent Pattern Tree |
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| Li Nai-qian,Shen Jun-yi,Song Qin-bao.Mining Generalized Association Rules Based on Frequent Pattern Tree[J].Mini-micro Systems,2002,23(12):1469-1471. |
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| Authors: | Li Nai-qian Shen Jun-yi Song Qin-bao |
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| Abstract: | The algorithm MGAR-FP for mining generalized association rules based on frequent pattern tree is proposed. It makes full use of the properties of frequent pattern tree and avoids producing a large number of candidate itemsets, so speeding up the mining. The experiments shows it is efficient and it's execution speed is faster than the traditional mining algorithm Cumulate. |
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| Keywords: | knowledge discovery data mining association rules generalization |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
