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Abstract
Knowledge Discovery through mining association rule among data from a large database is the one of key area of research. The first proposed Algorithm apriori is used to mine frequent items from the large database which leads to mine Association Rule between the data for discovering the Knowledge from the large database. Due to the limitation and complexity of Apriori algorithm, lot of research is underway for discovering new algorithms with a motive of minimizing the time and number of database scans for Knowledge Discovery through mining Association Rule among data from a large database. This paper propose one such kind of new algorithm which takes less number of scans to mining the frequent items from the large database which leads to mine the association rule between the data.
Keywords: Apriori, Confidence, Support, matrix, AND operation, frequent Item Set,Probablity
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1. Introduction
The challenging task is to extracting useful information from the large collection of data in Dataware house and data base. Around the world lot of research is underway to discover the knowledge from the large collection of data in data warehouse. In this process many algorithms has been proposed to identify the associations between the data in the database, leads to mine the association rule among the data. Association rules are used for knowledge discovery and to take useful managerial decision in the organization based on the results of associations among data stepping toward to make a smarter system. In this regard, the first algorithm Apriori [1] was proposed in the year 1994 by Agarwal and Srikanth to mine the frequent item set. Time constraint and efficiency of algorithms leads to lot of research in the area of o algorithm to build efficient algorithm which takes less time and few number of database scans to mine frequent Item set and association rule.
The first most famous algorithm Apriori is proposed in the year 1994 by Agarwal and Srikanth to mine the frequent item set, which leads to mine association rule. Apriori algorithm suffers from many numbers of database scans required to identify the frequent items set and take more time if the database size is increased. Then Partition algorithm was proposed, where instead scanning entire database and...