Data Cleaning System to Handle Noisy Data (International Journal of Engineering and Computer Science, 2015)
Data cleaning techniques are used for identification of record duplicates, missing data, and duplicate elimination. This paperpresents a data cleaning system, it goes through six steps: selection of attributes, formation of tokens, clustering algorithm, similaritycomputation, elimination function, and finally merge step. The system architecture contains three components: users interface, datacleaning, and reports component where they can communicate and cooperate with each other's. It is implemented using SQL Server 2010and Microsoft visual c# 2010.