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| 研究生： |
張元哲 Yuan-Che Chang |
|---|---|
| 論文名稱： |
FP-tree(Frequent Pattern Tree)的調整維護技術研究 |
| 指導教授： |
陳彥良
Yen-Liang Chen |
| 口試委員: | |
| 學位類別： |
碩士 Master |
| 系所名稱： |
管理學院 - 資訊管理學系 Department of Information Management |
| 畢業學年度： | 89 |
| 語文別： | 中文 |
| 論文頁數： | 51 |
| 中文關鍵詞： | 資料挖掘 |
| 外文關鍵詞： | Data Mining, association rules, FP-tree |
| 相關次數： | 點閱：9 下載：0 |
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然而上述的兩類方法都需要掃描資料庫兩次以上，在超大型的交易資料庫上進行這樣的動作將相當費時，因此如果能夠依照交易資料庫的異動情況，以incremental的方式修改large itemsets來維護association rules的正確性，又不需要重新掃描資料庫，便相當有價值。過去所提出的incremental維護方法，均是針對第(1)類方法所進行的研究，而第(2)類方法目前都還沒有人提出相關的incremental維護方法，本研究便是針對第(2)類方法中的FP-tree結構，提出incremental維護演算法FPI（FP-tree Incremental），可以在資料庫發生insert、delete或update時，不需要重新掃描整個資料庫即可很有效率地動態調整FP-tree，使它維持正確的結構。另外一種常見的情況是產生association rule的minimum support變小時，由於FP-tree並未包含原先minimum support下屬於infrequent item的node，故需要重新掃描資料庫來建構新的FP-tree，FPI在這種情況下也可以達到動態調整的目的，而不用浪費掃描整個資料庫的I/O時間來重新建構FP-tree。
由於FP-tree通常遠小於交易資料庫本身而可以放在主記憶體中，所以一旦完成FP-tree的建構，以FP-growth來產生frequent patterns就非常的迅速，因此它所花費的主要時間便在掃描資料庫的I/O和建構FP-tree之上，本研究所提供的FPI演算法可以即時地維護FP-tree正確結構，使association rules可以快速產生。
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