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.

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