| 关联分析研究的进展 |
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| 引用本文： | 陈宇珽,张保稳,何德全. 关联分析研究的进展[J]. 信息安全与通信保密, 2010, 0(2): 84-87 |
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| 作者姓名： | 陈宇珽 张保稳 何德全 |
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| 作者单位： | 上海交通大学,上海,200240 |
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| 摘 要： | 关联规则的发现是数据挖掘的一个重要方面，由于信息数据的急剧增长，面对浩如烟海的海量数据，为把这些数据转换成被人类充分利用的有价值信息，对关联规则挖掘算法进行研究就显得异常重要。总结了当今各种关联规则挖掘算法并对其加以分类，阐述了各类关联规则算法的特点，列举算法之间的差异，在时间和空间上进行比较，并且在此基础上对关联规则挖掘的未来趋势进行了分析和展望。
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| 关 键 词： | 数据挖掘 关联分析 Aprior算法 频繁项集 |
Research Progress on Association Analysis |
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| CHEN Yu-ting,ZHANG Bao-wen,HE De-quan. Research Progress on Association Analysis[J]. China Information Security, 2010, 0(2): 84-87 |
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| Authors: | CHEN Yu-ting ZHANG Bao-wen HE De-quan |
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| Affiliation: | CHEN Yu-ting,ZHANG Bao-wen,HE De-quan (Shanghai Jiaotong University,Shanghai 200240,China) |
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| Abstract: | The discovery of association rule is an important aspect of data mining. Due to the tremendous increase of information data and in order to transform these raw data into valuable information which could be best used by the people, it's extremely important to study the mining algorithm. The paper summarizes various prevailing association rule mining algorithms, classifies them into four different types and makes comparisons between among various types of algorithms. And based on this, the future developments... |
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| Keywords: | data mining association analysis Apriori frequent itemset |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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