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Intelligent online shopping cart which can automatically pre-load a shopping list

IP.com Disclosure Number: IPCOM000236206D
Publication Date: 2014-Apr-11

Publishing Venue

The IP.com Prior Art Database

Abstract

While shopping via electronic media like the internet, a user(purchaser) has to load a shopping cart by browsing through a catalog of items and selecting a list of items each time he initiates an electronic purchase transaction. If a user purchases some items repeatedly, process of searching and adding items to shopping cart has to be done during every single transaction. This is especially true in case of grocery shopping. It can be quite mundane and painful to enter a long list of items like groceries in to a shopping cart every time a user shops. Instead, if a shopping cart gets intelligently and automatically pre-loaded with a list of items that a user might want to purchase, it will help save time and effort for users. This article describes ways to automatically and intelligently pre-load shopping carts.

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Intelligent online shopping cart which can automatically pre -load a shopping list While shopping via electronic media like the internet,

a user(purchaser) has to load a shopping cart by browsing through a catalog of items and selecting a list of items each time he initiates an electronic purchase transaction. If a user purchases some items repeatedly, process of searching and adding items to shopping cart has to be done during every single transaction. This is especially true in case of grocery shopping. It can be quite mundane and painful to enter a long list of items like groceries in to a shopping cart every time a user shops. Instead, if a shopping cart gets intelligently and automatically pre-loaded with a list of items that a user might want to purchase, it will help save time and effort for users.

Before pre-loading a shopping cart, items that are likely to be purchased by a user have to be predicted in some way. This disclosure does not deal with ways/algorithms that are used to predict items. There are variety of algorithms already being used to predict items of interest for a user with varied degrees of certainty. These algorithms are sure to become more and more accurate as artificial intelligence, machine learning and data mining techniques improve, which is already happening at a very fast rate. However, at present, any items that are predicted as likely purchases are merely displayed to users to capture their attention to those items.

Once such items are displayed to a user, the user has to manually add those items to a shopping cart. The approach of the present disclosure is to automatically pre-load such items in to a shopping cart, there by helping users save time and effort. Algorithms used to predict items of interest to a user can be expected to be intelligent enough to make sure that only those items that are likely to be purchased are short listed for pre-loading. One such method is described in this paper:
"Predicting Customer Shopping Lists from Point of Sale Purchase Data" http://rayidghani.com/publications/kdd2004.pdf
How ever, please note that Rayidghani's paper only talks about predicting items and displaying them to a user as a suggested shopping list. It does not automatically pre-load a cart. It uses a PDA mounted on a physical shopping cart in a brick and mortar retail store as a means to display its suggestions to capture user's attention. User then has to use such a suggested list to manually add items to shopping cart. This is similar to how various internet websites display a list of items on their webpages to capture user's attention to those items. Even on such websites, user has to manually add any interesting items to shopping cart. So, Rayidghani's paper does not embody the idea of intelligent online shopping cart which can automatically pre-load shopping list as described in the present disclosure.

Another algorithm used to predict items that a user is likely going to purchase is describe...