Estimating Null Values in Relational Database Systems

• Main Authors: Che-Hsiung Yu, 余哲雄
• Other Authors: Chin-Tzong Pang
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/89539608479972233205

碩士 === 元智大學 === 資訊管理學系 === 95 === Good decision needs to be based on correct information.A database system will not operate properly if any null value of attributes exists. This result will often cause enterprises to lose its niche or even result in loss. To estimate null values in relational database systems is an important research topic. This paper proposes a method to estimate null values in relational databases. We use clustering algorithm to cluster data and then use fuzzy correlation coefficient and fuzzy coefficient of determination methods to calculate the correlation of different attributes; then we derive out each cluster the relative variation value among attributes, and use this relative variation value to derive out the estimation rule to each cluster; then compare the to-be-estimated data with the cluster center of each cluster to find out the closest cluster in terms of distance, followed by including the cluster to get the estimated value with the cluster''s estimation rule. The estimated result is calculated using clusters; therefore, time spending on comparison processing is significantly reduced and the calculated result is more accurate than existing estimation approaches.