Effectiveness of weighted graph of schema to aid the minimization and measurement of schema complexity

Golam Md. Muradul Bashir, Arpita Howlader, I. Shemu, E. Ety
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Abstract

Database system is used for access multiple users, prevent loss of data and provide security for access of real life or synthetic data set. The complexity of data requirement increasing day by day; therefore minimization of schema becomes an important role for equi distribution or equalization of two or more problems. We find the effect of normalization and de-normalization on minimization of schema of real life data model as well as synthetic data model. Schema complexity is measured by transmitting schema to a graph with weight or weighted graph. Selected special fundamentals from schema for weight the schema graph are described as major part. Minimization of schema ensures easy to measure the schema complexity. The purpose of this sightsee is to appraisal the effectiveness of weighted graph of schema to minimize as well as to measure the complexity.
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模式加权图的有效性,有助于最小化和测量模式复杂性
数据库系统用于访问多个用户,防止数据丢失,为现实生活或合成数据集的访问提供安全保障。数据需求的复杂性日益增加;因此,模式的最小化成为两个或多个问题的均衡分配或均衡的重要作用。我们发现了归一化和反归一化对现实数据模型和综合数据模型的模式最小化的影响。模式复杂度是通过将模式传输到带权重的图或加权图来度量的。从模式中选取特殊的基本要素进行加权,将模式图描述为主要部分。模式的最小化保证了模式复杂度的度量。本文的目的是评价模式加权图最小化的有效性,并衡量其复杂性。
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