PREDICTING MISSING ITEMS  IN SHOPPING CARTS


  predcting missing item in shopping carts.ppt (Size: 222 KB / Downloads: 0)


Introduction of Project:



Using the recently proposed data structure of item set trees (IT-trees), we obtain, in a computationally efficient manner, all rules whose antecedents contain at least one item from the incomplete shopping cart.
Then, we combine these rules by uncertainty processing techniques, including the classical Bayesian decision theory and a new algorithm based on the Dempster-Shafer (DS) theory of evidence combination


EXISTING SYSTEM


Research in association mining has focused mainly on how to expedite the search for frequently co-occurring groups of items in “shopping cart” type of transaction


PROPOSED SYSTEM


The prediction task was mentioned as early as in the pioneering association mining paper by Agrawal, but the problem is yet to be investigated in the depth it deserves.


To the latter task by proposing a technique that uses partial information about the contents of a shopping cart for the prediction of what else the customer is likely to buy
Proposed data structure of item set trees (IT-trees).


Register module


In this Module User Can give the personal Info these details will be insert in to database.
After registration he can get the user id and password.


Admin module


In this Module admin can login in to the system by giving user id and password after login he can add the item details and he can view the order details.