Time-Aware Item Weighting for the Next Basket Recommendations (2023-07-30T00:00:00.000000Z)

TL;DR

A novel method, Time-Aware Item-based Weighting (TAIW), which takes timestamps and intervals into account and outperforms well-tuned state-of-the-art baselines for next-basket recommendations.

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.

Authors

A. Romanov

1 papers

Oleg Lashinin

1 papers

Marina Ananyeva

1 papers

Time-Aware Item Weighting for the Next Basket Recommendations

TL;DR

Abstract

Authors

References27 items

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