Clustering based association rule mining on online stores for optimized cross product recommendation

摘要

The Online Shopping Experience has opened the new ways of business and shopping. Now the traditional terms of shopping have been changed and new terms to shop online emerge into customers' online shopping behaviors and preferences. Extracting interesting shopping patterns from ever increasing data is not a trivial task. We need intelligent association rule mining of the available data; that can be practically knowledgeable for the online retail stores, so that they can make viable business decisions. This paper will help to understand the importance of data mining techniques, i.e., association rules, clustering and concept hierarchy in order to provide business intelligence for improved sales, marketing and consumers' satisfaction.