A new method to estimate null values in relational database systems based on automatic clustering techniques

In this paper, we present a new method for estimating null values in relational database systems based on automatic clustering techniques. The proposed method clusters data in advance, such that it only needs to process the most proper clusters instead of all the data in the relational database syst...

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Bibliographic Details
Published in:	Information sciences Vol. 169; no. 1; pp. 47 - 69
Main Authors:	Chen, Shyi-Ming, Hsiao, Hsin-Ren
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 06.01.2005
Subjects:	Automatic clustering algorithm Fuzzy relation Null values Relational database systems Automatic clustering algorithm Null values Relational database systems Fuzzy relation
ISSN:	0020-0255, 1872-6291
Online Access:	Get full text
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Summary:	In this paper, we present a new method for estimating null values in relational database systems based on automatic clustering techniques. The proposed method clusters data in advance, such that it only needs to process the most proper clusters instead of all the data in the relational database system for estimating null values. The average estimated accuracy rate of the proposed method is better than the existing methods for estimating null values in relational database systems.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0020-0255 1872-6291
DOI:	10.1016/j.ins.2004.02.012