Live Session
Friday Posters
Main Track
Time-Aware Item Weighting for the Next Basket Recommendations
Aleksey Romanov (National Research University Higher School of Economics), Oleg Lashinin (Tinkoff), Marina Ananyeva (National Research University Higher School of Economics) and Sergey Kolesnikov (Tinkoff.AI).
Abstract
In this paper we study the next basket recommendation problem. Recent methods use different approaches to achieve better performance. However, many of them do not use information about the time of prediction and time intervals between baskets. To fill this gap, we propose a novel method, Time-Aware Item-based Weighting (TAIW), which takes timestamps and intervals into account. We provide experiments on three real-world datasets, and TAIW outperforms well-tuned state-of-the-art baselines for next-basket recommendations. In addition, we show the results of an ablation study and a case study of a few items.