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研究生:張耀升
研究生(外文):Yao-Sheng Chang
論文名稱:線上關聯規則採掘之資料方體挑選方法
論文名稱(外文):Efficient Data Cube Selection for Online Association Rules Mining
指導教授:林文揚林文揚引用關係
指導教授(外文):Wen-Yang Lin
學位類別:碩士
校院名稱:義守大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:91
語文別:中文
論文頁數:84
中文關鍵詞:資料倉儲資料採掘多維度資料庫線上分析處理資料方體啟發式演算法
外文關鍵詞:Data WarehousingData MiningMultidimensional DatabaseOLAPDatacubeHeuristic Method
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資料倉儲(Data Warehouse)是針對決策支援系統(Decision Support System,DSS)的需求所發展出的新一代資料庫的觀念,其資料通常經由線上分析處理(On-line Analytical Processing,簡稱OLAP),提供管理者決策時的參考。為縮短查詢的時間,並提供使用者不同的觀察角度,這些資料通常在某一主題的關聯下,以多維度的資料型式儲存,稱為資料方體(DataCube)。然而資料倉儲儲存的空間有限,無法儲存所有的資料方體,因此,如何在有限的儲存空間限制下,選取適當的子方體加以實體化,以縮短查詢的時間,是近來廣受探討的問題。
過去在這方面的研究都是針對一般的SQL查詢或OLAP分析,鮮少有針對資料採掘查詢,探討如何進行資料方體實體化的研究。本研究主要在探討如何利用資料方體技術,進行所謂的線上關聯規則採掘,其中關鍵在於如何挑選適當的資料方體加以儲存。針對此問題,我們明確定義利用資料方體來進行線上關聯規則採掘的模式及其查詢成本的估算方式,並運用多種啟發式挑選方法,在有限的儲存空間下挑選出最佳的資料方體的組合。

Data warehousing is a new database concept dedicated to supporting executive managers in decision-making through OnLine Analytical Processing (OLAP). To decrease the query time and provide various user viewpoints, these data usually are organized as a multiple dimensional data model, called data cubes. Each cell in a data cube represents one of the aggregations of manager’s concern. The data cube selection problem is, given the set of user queries and a storage space constraint, to select a set of materialized subcubes from the data cubes to minimize the query cost, such as response time and/or the maintenance cost.
In the past few years, most researches for this problem mainly focused on data cubes dedicated to SQL or OLAP queries. To our knowledge, there is no work addressing the data cubes selection issue for association query. In this thesis, we explore how to use materialized datacubes to facilitate online association rules mining. The most important key point is how to select suitable datacubes to materialize. To this end, we define a cost model for datacubes selection problem and elaborate the cost estimation for association query. Besides we propose various heuristic algorithms to select suitable datacubes subject to the space constrai

第一章 序論 1
1.1 研究動機 1
1.2 研究貢獻 3
1.3 章節安排 4
第二章 背景知識與相關研究 5
2.1 資料倉儲 5
2.2 資料方體(Data Cube)與線上分析處理(On Line Analytical Processing OLAP) 7
2.3 相關研究 14
第三章 理論架構與問題定義 17
3.1 多維度關聯規則 17
3.2 使用於關聯規則查詢之資料方體 20
3.3 問題的定義 21
第四章 OLAP式的關聯規則採掘及查詢成本估算 22
4.1 OLAP資料方體與關聯規則的對應關係 22
4.2 以OLAP資料方體進行多維度關聯規則採掘 25
4.2.1 維度內關聯規則 25
4.2.2 維度間關聯規則 33
4.2.3 混合式關聯規則 40
4.3 查詢成本估算 48
4.3.1 維度內關聯規則 49
4.3.2 維度間關聯規則 53
4.3.3 混合式關聯規則 55
第五章 啟發式資料方體挑選方法 59
5.1 正向貪婪挑選法 59
5.2 反向貪婪挑選法 62
5.3 體積挑選法 65
第六章 實驗分析 67
6.1 值實驗 67
6.2 各線上關聯規則之資料方體挑選法分析 67
6.2.1 維度內關聯規則之挑選比較 69
6.2.2 維度間關聯規則之挑選比較 70
6.2.3 混合式關聯規則之挑選比較 71
6.2.4 多維度關聯規則之挑選時間比較 72
第七章 結論及未來工作 73
參考文獻 74

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