• V. Malsoru
• Dr. R. Jegadeesan
• D.Tejaswini
• V. Shivani
• A.Anusha

Generic dataset mining with differential private indicates to the matter of extracting all generic object sets whose supports unit of measurement over a given threshold terribly very given transaction dataset, with the condition that the extracted results mustn't violate the security of any single human activity. present solutions for this drawback cannot well balance effectiveness, security, and data usage over massive scale information. Toward this end, we tend to propose associate economical, differential private generic datasets mining rule over massive-scale information. supported the ideas of sampling and human activity truncation mistreatment length conditions, our rule decreases the computational strength, decreases mining reactivity, and so increases data usage given a tough and quick privacy budget. Priliminary results show that our rule gain higher performance than previous approaches on various object sets.

generic item set, Intensity, potency

"GENERIC ITEM SET MINING WITH DIFFERENTIAL PRIVACY OVER MASSIVE SCALE INFORMATION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.324-328, March-2019, Available :http://www.jetir.org/papers/JETIRAU06045.pdf

"GENERIC ITEM SET MINING WITH DIFFERENTIAL PRIVACY OVER MASSIVE SCALE INFORMATION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp324-328, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06045.pdf