i need ppt for prediction of missing items in online shopping
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Existing research in association mining has focused mainly on how to accelerate the search for frequently coexisting groups of elements in the type of transaction type transactions; Less attention has been paid to methods that exploit these items of frequent articles for predictive purposes. This work contributes to this latter task by proposing a technique that uses partial information on the contents of a shopping cart to predict what else the customer is likely to buy. Using the recently proposed data structure of itemset trees (IT-trees), we obtain, in a computationally efficient way, all rules whose antecedents contain at least one incomplete cart element. We then combine these rules with uncertainty processing techniques, including classical Bayesian decision theory and a new algorithm based on the Dempster-Shafer (DS) theory of combination of tests.
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