• S.Srilekha
• M.Amulya
• Dr. R. Jegadeesan
• Ch.Anil
• G.Mahesh

The frequent item set mining will not address both the quantity and profit of the item sets. The high utility itemset mining is an emerging area of mining which considers and addresses the quantity and profit of the item sets in the database. High utility itemset mining is done efficiently by using the SPHUI-Mining algorithm, which reduces the time and space complexity by using the reduced transaction pattern list (RTPL) and projects the reduced transaction pattern list. Selective projections of the database used in the SPHUI-mining algorithm plays a major role in reducing the scanning time of the database, which makes the approach more effective. Most challenging part of the HUI mining is the exponential complexity in both time and space. HUIM is used in wide range of applications, such as the analysis of clickstream on websites, mobile computing, finding top-k itemsets and biomedical applications

Data mining, frequent itemset mining, high utility mining, database projection.

"GENERATING HIGH UTILITY PATTERNS FROM LARGE DATA SETS USING REDUCED TRANSACTION PATTERN LIST ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.221-229, March-2019, Available :http://www.jetir.org/papers/JETIRAU06033.pdf

"GENERATING HIGH UTILITY PATTERNS FROM LARGE DATA SETS USING REDUCED TRANSACTION PATTERN LIST ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp221-229, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06033.pdf