Frequent Patterns Discovery over Big Transactional Data Set using ‘Divide and Conquer’ and Apriori2
Finding frequent patterns proven to be more informative for organizations where frequent patterns play a dominant role for improving the productivity and profitability, in-order to capture the market both socially and economically to the best. Many effective algorithms were introduced for extracting frequent patterns. One among those Apriori is an effective algorithm for extracting frequent patterns. As data is increasing enormously in this era, Big Data; finding frequent patterns using standard Apriori algorithm is sluggish. To prevail over this, Divide and Conquer integrated with standard Apriori algorithm explored to be more promising in recent discovery. This paper furnishes this recent discovery by including Apriori2 instead of standard Apriori along with Divide and Conquer. Also it contains incremental discovery of residue patterns which may be frequent or infrequent. These residues undergo test for determination as frequent patterns.