An Innovative Approach for Finding Frequent Item Sets Using Maximal Apriori and Fusion Process and Its Evaluation
Frequent pattern mining is a vital branch of Data Mining that supports frequent itemsets, frequent sequence and frequent structure mining. The authors' approach is regarding frequent itemsets mining. Frequent item sets mining plays an important role in association rules mining. Many algorithms have been developed for finding frequent item sets in very large transaction databases. This paper proposes an efficient Sort Recursive Mine (Sorted and Recursive Mine) Algorithm for finding frequent item sets. This proposed method reduces the number of scans in the database by first finding the maximal frequent itemsets in the database and then all its subset consider as frequent according to Apriori property.