Generating Association rules to identify frequent patterns in E-Commerce

Abstract

Internet emerged as one of the important tools of communication in the recent years and E-commerce has gradually grown with it and has given rise to a new world of doing business. It has drawn attention to apply data mining techniques to identify frequent patterns for improving business strategies. The main aim of Frequent pattern discovery is to find frequently occurring itemsets in large databases. Frequent pattern mining is the most important step in mining association rules to show items that have same patterns in the database, appear together. In E-commerce, frequently occurring product purchase combinations are essential to model user preference. In this paper we look at the existing algorithms which are used to identify the association rules and discusses how they are extend to find frequent patterns in E-commerce.