Abstract
This paper presents a new algorithm for recommender systems applied to smart carts. As the customers pass through the store's aisles, they place their desired products in their cart baskets. In many instances, the customers pick an item from the shelf and place it in the basket but after a while they find a similar item with different specifications. The difference may be in price, quality, weight or other factors. In our proposed plan, based on the customer's decision from choosing the first item and replacing it with another item from the same group, there will be an attempt to identify the customer's taste and accordingly recommend a third, fourth, etc., item that might also meet his/her needs. The complete algorithm is introduced as a systematic procedure and the implementation results are shown. The proposed recommender system is designed based on the features of smart carts. We have simulated a part of the smart cart in an application, named NIKSHIRI-Shop, using C# and SQL.
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