Analysis of Customer Buying Behavior using Equivalence Class Transformation (ECLAT)

Abstract

Many organizations are being interested in mining association rules from business records because they desire to promotethe benefit from large amount of data that are continuously stored in databases. Discovery of frequent itemsets through transactional records can support very useful idea and advice in business decision making processes. Mining association rules from transactions is important in business called market basket analysis. It helps the administrative level for making effective decisions.This system is intended to develop for analyzing the correlation of different items that are frequently buying together in a grocery store. Equivalence Class Transformation (ECLAT) is one of the best algorithms to identify which products are frequently bought together.Such sets of associated products can be used to optimize the offered products on the displayed stands.Therefore, this system can give guide lines with valuable advices to managers who are managing the arrangement of the items in grocery store.