属性粒度数据质量模型及其评价指标研究  

Data Quality Model and Metrics Research at Attribute Granularity

作　　者：陈卫东[1] 张维明[1] 

机构地区：[1]国防科技大学信息系统与管理学院,长沙410073

出　　处：《计算机科学》2010年第5期139-142,共4页Computer Science

摘　　要：在研究属性粒度关系代数传递影响的基础上,进一步从数据质量正确性和完整性两方面加以总结,提出一个数据质量评价模型,以区分5种元组质量类型,定义正确性和完整性指标同时包含数据项和元组两个方面带来的影响。通过分析空值,即不正确也不完整,建立正确性和完整性指标的相互联系,进而引入属性量化前后错误(空值)率,进一步量化定义评价指标。Based on the author＇s previous research at data quality propagation for relational database, the paper sumed up and presented a data quality model at attribute granularity, which both considers the influence of accuracy and completeness. According to the model, the tuples were classified into five categories. The definitions of accuracy and completeness both include the influence of the data item and tuple. After analysing the null data neither correct nor complete, the mutual relationship between them was formed. Then the attribute error rate before and after quantitative was introduced to define metrics further.

关 键 词：数据质量 质量模型 正确性 完整性 关系数据库 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]