Abstract
With the easy availability of shopping transaction data, it is now possible to use historical information to enhance the shopping experience of shoppers. In particular, we focus on the issue of forgotten items. We have all had the experience of shopping at a supermarket and either forgetting to buy certain items or not realizing that certain items are needed. In this paper, we focus on predicting such items during a shopper’s visit and providing hints to the shopper that they may in fact need certain items that were not purchased. Note that, by providing hints for forgotten items, the shopper benefits by avoiding a return trip to the supermarket and the supermarket benefits because the shopper purchases additional items. We provide examples to illustrate the utility of the proposed approach.
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Singh, A., Hosein, P. (2020). On the Prediction of Possibly Forgotten Shopping Basket Items. In: Hemanth, D., Kose, U. (eds) Artificial Intelligence and Applied Mathematics in Engineering Problems. ICAIAME 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 43. Springer, Cham. https://doi.org/10.1007/978-3-030-36178-5_45
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DOI: https://doi.org/10.1007/978-3-030-36178-5_45
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