In reality the data set may have at least one portrayal of a similar certifiable elements. Duplicate may emerge because of exchange errors and because of deficient information. Expelling such duplicate, all things considered, is a perplexing errand.
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It isn't direct to productively discover and expel the duplicates from a vast data set. This paper center around correlation with conventional duplicate discovery strategies Incremental Sorted Neighborhood Method (ISNM) and the Duplicate Count Strategy (DCS++) technique with Progressive Sorted Neighborhood Method (PSNM) technique.
by S. Divya "A Novel Approach for Progressive Duplicate Detection for Quality Assurance"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd12972.pdf
Direct Link - http://www.ijtsrd.com/computer-science/other/12972/a-novel-approach-for-progressive-duplicate-detection-for-quality-assurance/s-divya
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