Foundation for Interdisciplinary Research in Engineering (FIRE)
In recent times, data mining plays one of the decisive role in business intelligence. Analyzing enormous amount of business transaction data is the order of the hour. Association rule learning is one of the major part in data mining that helps them to attain functional patterns understanding buying habits which can help in business decision making, increasing revenues, cutting cost etc. Apriori algorithm is one of the well-researched measure to generate association rules which are related set of data existing in transaction data. In this paper, the authors present an enhanced approach of market basket analysis under the framework of improved probability based association rule learning using the notion of apriori algorithm.