Implementation OF AM_ebiz Algorithm for finding Frequent Itemsets

In recent years, knowledge discovery has been focused on advancements with the vision of benefits to the corporate sector. This research work explicates the concepts of data mining, especially the importance of Frequent Pattern Mining (FPM) and Hadoop MapReduce programming model. The organization sectors such as social networks, web browsing, telecommunication, utilities, transportation, insurance, banking and many others generate vast amount of data every day. The proposed work for frequent item set mining of large volume of data is different from all the previous works, since it uses AM e_biz Algorithm with map reduce programming model. It provides compressed storage facility, reduced execution time. It is applicable in many of data mining applications like market-basket problem, decision support, web usage mining, and bioinformatics.