Predicting Missing Items in a Shopping Cart using Positional Mining Algorithm

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Kanna Sandhya Laxmi
T.P.Shekhar, K. Sai Krishna


Prediction in shopping cart uses partial information about the contents of a shopping cart for the prediction of what else the customer is likely to buy. Existing representation uses Itemset Tree (IT-tree) data structure, all rules whose antecedents contain atleast one item from the incomplete shopping cart generated. This paper uses a new concept of “Positional Lexicographic Tree†(PLT) with which frequ-ent itemsets are generated. Association rules are to be generated from the already generated frequent itemsets by using Positional Mining Algorithm.Then, we combine these rules by using Dempster-Shafer (DS) theory of evid-ence combination. Finally the predicted items are genera-ted to the user.



Keywords: Frequent Itemsets, Association Rule Mining, Positional Lexicographic Tree, Prediction,Positional Mining Algorithm, Dempster-Shafer Theory of Rule Combination.


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