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