(untitled) (International Journal of Engineering and Computer Science, 2017)
The project aims on frequent itemset mining, which focuses on discovering the different correlations among data. The itemsets that became rare are no longer extracted using frequent generalized itemsets from a certain point. Frequent generalized itemsets includes itemsets that are frequently occurring in source data and itemsets that provide a top level abstraction of the knowledge that is mined. The discovery of relevant data occurrences and their most significant temporal trends are becoming very essential and important research area. In different application contexts the correlation among data has been found out by the application of frequent itemset mining and association rule extraction algorithms. Here provides several query optimization strategies for extended queries and describes an algorithm which includes query execution with performance evaluation while making use of native query engine. I