Partitional approach for estimating null value in relational database

Authors:
Jia-Wen Wang;Ching-Hsue Cheng;Wei-Ting Chang
Affiliations:
Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan, R.O.C;Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan, R.O.C;Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan, R.O.C
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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

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Abstract

In this paper, we propose a partitional approach for estimating null value (1) Firstly, we utilize stepwise regression to select the important attributes from the database. (2) Secondly, we use a partitional approach to build the data category. The data partitioned by the first two important attributes. (3) Thirdly, we apply the clustering method to cluster output data. (4) Fourthly, Calculate the degree of influential between the attributes. There are two ways to calculate the degree of influential. One is correlation coefficient and the other is regression coefficients. (5) To verify our method, this paper utilizes a practical human resource database in Taiwan, and Mean of Absolute Error Rate (MAER) as evaluation criterion to compare with other methods; it is shown that our proposed method proves better than other methods for estimating null values in relational database systems.