An Enhanced Prediction Technique for Missing Itemset in Shopping Cart

The goal of frequent pattern mining is to determine the frequently occurring group of items in the databases. Here the major contributing task is expediting the frequent itemset by proposing a technique that uses the minimal data available in the shopping cart for the prediction of what other items the customer can get the choice to buy. Several algorithms have been implemented to detect the frequently co occurring group of items in the transactional databases for prediction purposes. This paper introduces a new technique whose principal diagonal elements represent the association among items and looking to the principal diagonal elements, the customer can select what else the other items can be purchased with the current contents of the shopping cart and also reduces the rule mining cost. Keywords—Association rule mining, Data mining, Frequent itemset mining, Prediction.