基于D-S证据理论的不确定数据清洗

数据清洗的任务是检测数据中存在的错误、缺失或不一致,通过删除、填充、修改等方法提高数据质量.针对存在元组级不确定性的数据表上的选择投影连接操作,基于D-S证据理论中置信区间的概念,给出辨识框架构建和置信区间计算的方法,提出了一种基于待测数据项置信区间来检测查询结果中错误数据的方法.实验结果表明,提出的不确定数据错误检测方法具有高效性、准确性和可用性.

Cleaning uncertain data based on the D-S evidence theory

Data cleansing is to detect errornous,missing or inconsistent data,which can be removed,filled or corrected to improve data quality.Aiming at the selection-projection-join operations on the tuple-level uncertain data tables,in this paper we gave the algorithms for constructing Frames of Discernment and computing the evidence intervals based on the corresponding concepts in the D-S evidence theory.Then,we proposed the method for detecting errornous data in the query results based on the evidence interval of the target data items.Experimental results show that our proposed method is efficient,accurate and applicable.