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臺灣博碩士論文加值系統

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研究生:張舒婷
研究生(外文):Shu-Ting Chang
論文名稱:根據自動分群演算法及多迴歸分析技術以在關聯式資料庫系統中估計空值之新方法
論文名稱(外文):Estimating Null Values in Relational Database Systems Using Automatic Clustering and Multiple Regression Techniques
指導教授:陳錫明陳錫明引用關係
指導教授(外文):Shyi-Ming Chen
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:資訊工程系
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:2008
畢業學年度:96
語文別:英文
論文頁數:92
中文關鍵詞:關連式資料庫空值自動分群演算法分群中心
外文關鍵詞:Relational databaseNull valueAutomatic clustering algorithmCluster center
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  • 被引用被引用:0
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在本論文中,我們提出一個新的自動分群演算法及利用多迴歸分析技術以在關聯式資料庫系統中估計空值。首先,我們針對數值資料提出一自動分群演算法.本論文所提之自動分群演算法不須事先定義群數及也不須事先將資料予以排序,使得分群時能更有彈性。依據本論文所提出之自動分群演算法所做的分群結果來估計空值,其僅須針對其中一個分群的資料做估計空值的工作,無須針對整個資料庫系統內所有的資料做處理,本論文所提之在關聯式資料庫系統中估計空值的方法比目前已存在的方法具有更高的平均估計準確率。
In this thesis, we present a new method for estimating null values in relational database systems using automatic clustering and multiple regression techniques. First, we present a new automatic clustering algorithm for clustering numerical data. The proposed automatic clustering algorithm does not need to determine the number of clusters in advance and does not need to sort the data in the database in advance. Then, based on the proposed automatic clustering algorithm and multiple regression techniques, we present a new method to estimate null values in relational database systems. The proposed method for estimating null values in relational database systems only needs to process a particular cluster instead of the whole database. It gets a higher average estimation accuracy rate than the existing methods for estimating null values in relational database systems.
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Related Literature 2
1.3 Organization of This Thesis 2
Chapter 2 Fuzzy Set Theory 4
2.1 Basic Concept of Fuzzy sets 4
2.2 Types of Membership Functions 4
2.3 Summary 7
Chapter 3 A Method for Estimating Null Values in Relational Database Systems 8
3.1 Chen-and-Yeh’s Automatic Clustering Algorithm [12] 8
3.2 Hsiao-and-Chen’s Method to Estimated Null Values in Relational Database
Systems [18] 9
3.2.1 An Automatic Clustering Algorithm [18] 9
3.2.2 A Review of Chen-and-Hsiao’s Method for Estimating Null Values in
Relational Database Systems [17] 15
3.2.3 A Review of Chen-and-Chen’s Method for Estimating Null Values in
Relational Database Systems [9] 17
3.3 Summary 20
Chapter 4 A New Method for Estimating Null Values in Relational Database
Systems Using Automatic Clustering and Multiple Regression Techniques 22
4.1 A New Automatic Clustering Algorithm 22
4.2 A New Method to Estimate Null Values in Relational Database Systems 38
4.3 An Example of Estimating Null Value in Relation Database Systems 43
4.4 Summary 50
Chapter 5 Estimating Null Values in Relational Database Systems with
Negative Dependency Relationships between Attributes 52
5.1An Example of Estimating Null Values in Relational Database Systems
with Negative Dependency Relationships between Attributes 52
5.2A New Method to Estimate Null Values in Relational Database Systems
with Negative Dependency Relationships between Attributes 65
5.3 Summary 86
Chapter 6 Conclusions 87
6.1 Contributions of This Thesis 87
6.2 Future Research 87
References 89
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