• Jeevan Saraf
• Vipul Munot
• Sahil Patil
• Dr. Vijaykumar Bidve

Data mining is a computerized process of searching for models in large data sets that involve methods at the intersection of the database system. The popular problem of data mining is the extraction of high utility element sets (HUI) or, more generally, the extraction of public services (UI). The problem of HUI (set of elements of high utility) is mainly the introduction to the set of frequent elements. Frequent pattern mining is a widespread problem in data mining, which involves searching for frequent patterns in transaction databases. Solve the problem of the set of high utility elements (HUI) with some particular data and the state of the art of the algorithms. To store the HUI (set of high utility elements) many popular algorithms have been proposed for this problem, such as "Apriori", FP growth, etc., but now the most popular TKO algorithms (extraction of utility element sets) K in one phase) and TKU (extraction of elements sets Top-K Utility) here TKO is Top K in one phase and TKU is Top K in utility. In this paper, address previous issues by proposing a new frame work for k upper HUI where k is the desired number of HUI to extract. Extraction of high utility element sets is an uncommon term. But we are using it while shopping online, etc. It is part of the business analysis. The main area of application is the analysis of the market basket, where when the customer buys the item user can buy another to maximize the benefit both the customer and supplier profit.

Utility mining, high utility item set, top k Pattern mining, top k high item set mining.

"EFFICIENT HYBRID ALGORITHM FOR HIGH UTILITY ITEMSET MINING. ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.61-65, May-2019, Available :http://www.jetir.org/papers/JETIR1905M12.pdf

"EFFICIENT HYBRID ALGORITHM FOR HIGH UTILITY ITEMSET MINING. ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp61-65, May-2019, Available at : http://www.jetir.org/papers/JETIR1905M12.pdf