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| 快速更新全局频繁项目集 |
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杨明1,2, 孙志挥1, 宋余庆1,3
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1.东南大学,计算机科学与工程系,江苏,南京,210096;2.安徽工程科技学院,计算机科学与工程系,安徽,芜湖,241000;3.江苏大学,计算机科学与通信工程学院,江苏,镇江,212023
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| 摘要: |
| 数据挖掘中的频繁项目集更新算法研究是重要的研究课题之一.目前已有的频繁项目集更新算法主要针对单机环境,有关分布式环境下的全局频繁项目集的更新算法的研究尚不多见.为此,提出了快速更新全局频繁项目集算法(fast updating algorithm for globally frequent itemsets,简称FUAGFI).该算法主要考虑数据库记录增加时全局频繁项目集的更新情况.FUAGFI利用已建立的各局部频繁模式树(frequent pattern tree,简称FP-tree)及已挖掘的全局频繁项目集,可有效地降低网络通信量,提高全局频繁项目集的更新效率.实验结果表明,所提出的更新算法是行之有效的. |
| 关键词: 数据挖掘 分布式数据库 全局频繁项目集 频繁模式树(FP-tree) 更新 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.79970092 (国家自然科学基金); the Natural Science Foundation of Anhui Province of China under Grant No.03042205 (安徽省自然科学基金) |
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| Fast Updating of Globally Frequent Itemsets |
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YANG Ming,SUN Zhi-Hui,SONG Yu-Qing
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| Abstract: |
| The incremental updating research of frequent itemsets is an important data mining problem in data mining fields. Many sequential algorithms have been proposed for incremental updating of frequent itemsets. However, very little work has been done in updating frequent itemsets in distributed environment. In this paper, the algorithm FUAGFI (fast updating algorithm for globally frequent itemsets) is introduced in the case of inserting, which efficiently utilizes the created locally frequent pattern trees and the mined globally frequent itemsets. Therefore, FUAGFI uses far less communication overhead and obviously improves updating efficiency of globally frequent itemsets. Experimental results show the feasibility and effectiveness of the algorithm. |
| Key words: data mining distributed database globally frequent itemset frequent pattern tree (FP-tree) update |
