Duplicate Detection for Protein Data Using Simple Close Algorithm

Abstract

Due to the exploratory nature of biological database commercial and publicly, they are invited some drawback such as inaccurate, incomplete, duplicate and outdated of the genome data. Some work must be done to maintain quality data in genome data. Our objective in this paper is to provide a duplicate detection framework which focus on duplicate records in a real world Mice data protein database using simple close algorithm (SCA). SCA is an enhancement of work where they used a priori algorithm to generate the rule. In our approach we used matrix structure to represent data in a database. We implement SCA using Java programming language on 1.4 GHz Pentium 4 PC machine. As a result we show SCA can produces less duplicate rule (non-redundant) than a priori without loss of information and also improves the execution time