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研究生: 李蕙君
Huei-Jyun Li
論文名稱: 資料流最近常見項目集變動探勘之研究
Mining Recently Frequent Itemsets Change over Data Streams
指導教授: 柯佳伶
Koh, Jia-Ling
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2009
畢業學年度: 97
語文別: 中文
論文頁數: 64
中文關鍵詞: 資料流滑動視窗資料探勘
英文關鍵詞: data stream, sliding window, data mining
論文種類: 學術論文
相關次數: 點閱:167下載:4
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  • 本論文針對資料流滑動視窗的模型提出一個探勘狀態變動項目集的方法,稱為CV-SCD(Cross-Verify Status Change Detection)演算法。本方法主要利用兩棵稱為Base-Tree及Delta-Tree的相同字首樹之樹狀結構,儲存在任一時間點t時滑動視窗中所有交易資料,以及從t到t+1之間新增及過時的交易資料,並利用Base-Tree及Delta-Tree的資訊判斷出狀態變動項目集,再同時對兩棵樹遞迴建立包含特定項目的條件樹,以探勘出更長的狀態變動項目集。本論文對固定區間長度探勘出的狀態變動項目集儲存成狀態變動資料項集快照,並採用金字塔式時間框架的結構來儲存快照,提供可由使用者指定特定時間區間對其中各狀態變動項目集的變動情形進行相對特性分析。實驗結果顯示,當新增及過時的交易資料相對於滑動視窗資料為少量,或是資料集中包含之項目種類較多,或是在支持度小的情況下,CV-SCD演算法相較於以FP-growth探勘出常見項目集後再進行狀態變動項目集比對可顯著增進執行效率。

    In this thesis, a method for discovering recently status-changed itemsets over data streams is proposed, which is named the CV-SCD (Cross-Verify Status Change Detection) algorithm. In this algorithm, two prefix tree structures, which are named Base-Tree and Delta-Tree, respectively, are constructed for maintaining the transaction data in a sliding window at time t, and the newly inserted and removed transactions at time t+1. The data stored in the Base-Tree and Delta-Tree is used to discover the status-changed itemsets at t+1 with respect to t. By performing cross-verification on Delta-Tree and Base-Tree, then by constructing conditional Delta-Tree and conditional Base-Tree recursively, all the status-changed itemsets are discovered in depth-first search. The discovered status-changed itemsets within a fixed time interval are stored in a snapshot of status-changed itemsets. Accordingly, given a specific period of time interval, the changing characteristics of itemsets in this interval can be compared relatively.
    The experiment results show that FP-growth to discover all the frequent itemsets at each time point and then performing itemsets matching to get status-changed itemsets, the CV-SCD algorithm provides significant improvement on execution time when the added and expired transactions are few, or there are many different items in transaction data, or the support is small.

    附表目錄...................................................I 附圖目錄...................................................II 第一章 緒論................................................1 1-1 研究背景與研究動機..................................1 1-2 文獻探討...........................................3 1-3 論文方法...........................................10 1-4 論文結構...........................................11 第二章 背景知識及問題定義....................................12 2-1 背景知識...........................................12 2-2 狀態變動項目集探勘..................................14 第三章 資料流常見項目集變動探勘..............................16 3-1 交易資料儲存結構...................................16 3-2 狀態變動項目集探勘處理..............................20 第四章 狀態變動項目集儲存及分析..............................31 4-1 狀態變動資料項集快照................................31 4-2 項目集變動特性分類..................................33 4-3 快照儲存結構.......................................37 第五章 實驗效能評估.........................................41 5-1 實驗測試資料.......................................41 5-2 實驗評估...........................................42 5-3 實驗結果總結.......................................51 第六章 結論................................................52 參考文獻...................................................54

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