Time-Aware ItemWeighting for the Next Basket Recommendations

被引：0

作者：

Romanov, Aleksey ^{[1
]}

Lashinin, Oleg ^{[2
]}

Ananyeva, Marina ^{[1
]}

Kolesnikov, Sergey ^{[2
]}

机构：

[1] Natl Res Univ Higher Sch Econ, Moscow, Russia

[2] Tinkoff, Moscow, Russia

来源：

PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023 | 2023年

关键词：

Next-basket recommendation; Repeat consumption; Hawkes process;

D O I：

10.1145/3604915.3608859

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：985 / 992

页数：8

共 33 条

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