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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34210
標題: | 封閉性跨交易頻繁項目集合之資料探勘 An Efficient Algorithm for Mining Closed Frequent Inter-transaction Itemsets |
作者: | Wan-Yu Weng 翁婉玉 |
指導教授: | 李瑞庭 |
關鍵字: | 資料探勘,關聯規則,跨交易項目集合,封閉性項目集合, data mining,association rules,inter-transaction itemsets,closed itemsets, |
出版年 : | 2006 |
學位: | 碩士 |
摘要: | 跨交易關聯規則可代表不同交易中項目間的關係,而近年來有愈來愈多相關的探勘演算法被提出,然而這些演算法會產生相當多的跨交易頻繁項目集合。找尋封閉性跨交易頻繁項目集合可使探勘的過程更有效率。
因此,在本篇論文中我們提出了一個探勘演算法叫「ICMiner」,以找尋封閉性跨交易頻繁項目集合。我們的方法可分為兩個階段。第一階段,將原始的資料庫轉換成領域屬性集合,使得每一個頻繁項目的領域屬性形成一個集合。第二階段,利用ID-tree去列舉出所有的封閉性跨交易頻繁項目集合。藉由ID-tree進行資料探勘,我們可以避免產生候選樣式及重複計算支持度。因此,ICMiner可大幅提升了找尋跨交易頻繁項目集合的效率。實驗結果顯示,ICMiner比FITI與ClosedPROWL快上幾十倍。 Many algorithms have been proposed recently for finding inter-transaction association rules, which represent the relationships among itemsets across different transactions. Since numerous frequent inter-transaction itemsets will be generated, mining closed frequent inter-transaction itemsets can speed up the mining process. Therefore, in this thesis, we propose an algorithm, ICMiner (Inter-transaction Closed patterns Miner), to mine closed frequent inter-transaction itemsets. Our proposed algorithm consists of two phases. First, we convert the original transaction database into a set of domain attributes, datset, for each frequent item. Second, we enumerate closed frequent inter-transaction itemsets by using an itemset-datset tree, ID-tree. Mining closed frequent inter-transaction itemsets with an ID-tree, we can avoid costly candidate generation and repeatedly support counting. The experimental results show that our proposed algorithm outperforms the FITI and ClosedPROWL algorithms by one order of magnitude. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34210 |
全文授權: | 有償授權 |
顯示於系所單位: | 資訊管理學系 |
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