research-article

ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping

Authors:

Mozhdeh Ariannezhad,

Sebastian Schelter,

Maarten de RijkeAuthors Info & Claims

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 1240 - 1250

https://doi.org/10.1145/3477495.3531708

Published: 07 July 2022 Publication History

Abstract

Retailers such as grocery stores or e-marketplaces often have vast selections of items for users to choose from. Predicting a user's next purchases has gained attention recently, in the form of next basket recommendation (NBR), as it facilitates navigating extensive assortments for users. Neural network-based models that focus on learning basket representations are the dominant approach in the recent literature. However, these methods do not consider the specific characteristics of the grocery shopping scenario, where users shop for grocery items on a regular basis, and grocery items are repurchased frequently by the same user.

In this paper, we first gain a data-driven understanding of users' repeat consumption behavior through an empirical study on six public and proprietary grocery shopping transaction datasets. We discover that, averaged over all datasets, over 54% of NBR performance in terms of recall comes from repeat items: items that users have already purchased in their history, which constitute only 1% of the total collection of items on average. A NBR model with a strong focus on previously purchased items can potentially achieve high performance. We introduce ReCANet, a repeat consumption-aware neural network that explicitly models the repeat consumption behavior of users in order to predict their next basket. ReCANet significantly outperforms state-of-the-art models for the NBR task, in terms of recall and nDCG. We perform an ablation study and show that all of the components of ReCANet contribute to its performance, and demonstrate that a user's repetition ratio has a direct influence on the treatment effect of ReCANet.

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Cited By

Naghiaei MDehghan MRahmani HAzizi JAliannejadi MOosterhuis HBast HXiong C(2024)Personalized Beyond-accuracy Calibration in RecommendationProceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3664190.3672507(107-116)Online publication date: 2-Aug-2024
https://dl.acm.org/doi/10.1145/3664190.3672507
Katz OBarkan OKoenigstein N(2024)Personalized Cadence Awareness for Next Basket RecommendationACM Transactions on Recommender Systems10.1145/36528633:1(1-23)Online publication date: 2-Aug-2024
https://dl.acm.org/doi/10.1145/3652863
Coppens IDe Pessemier TMartens L(2024)Balancing Habit Repetition and New Activity Exploration: A Longitudinal Micro-Randomized Trial in Physical Activity RecommendationsProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3691715(1147-1151)Online publication date: 8-Oct-2024
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Index Terms

ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems
    2. Users and interactive retrieval
      1. Personalization

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cover image ACM Conferences

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2022

3569 pages

ISBN:9781450387323

DOI:10.1145/3477495

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Published: 07 July 2022

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SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 11 - 15, 2022

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Cited By

Naghiaei MDehghan MRahmani HAzizi JAliannejadi MOosterhuis HBast HXiong C(2024)Personalized Beyond-accuracy Calibration in RecommendationProceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3664190.3672507(107-116)Online publication date: 2-Aug-2024
https://dl.acm.org/doi/10.1145/3664190.3672507
Katz OBarkan OKoenigstein N(2024)Personalized Cadence Awareness for Next Basket RecommendationACM Transactions on Recommender Systems10.1145/36528633:1(1-23)Online publication date: 2-Aug-2024
https://dl.acm.org/doi/10.1145/3652863
Coppens IDe Pessemier TMartens L(2024)Balancing Habit Repetition and New Activity Exploration: A Longitudinal Micro-Randomized Trial in Physical Activity RecommendationsProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3691715(1147-1151)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3691715
Tran VSalha-Galvan GSguerra BHennequin R(2024)Transformers Meet ACT-R: Repeat-Aware and Sequential Listening Session RecommendationProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688139(486-496)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688139
Li JSun AMa WSun PZhang M(2024)Right Tool, Right Job: Recommendation for Repeat and Exploration Consumption in Food DeliveryProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688119(643-653)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688119
Tandoi MSolis Morales D(2024)Explore versus repeat: insights from an online supermarketProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688050(787-789)Online publication date: 8-Oct-2024
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Zou TMao YYe JDu BBaeza-Yates RBonchi F(2024)Repeat-Aware Neighbor Sampling for Dynamic Graph LearningProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3672001(4722-4733)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3672001
Coppens IDe Pessemier TMartens LBoratto LGena CMarras MGermanakos PPopescus E(2024)Repeating my Workouts or Exploring new Activities? A Longitudinal Micro-Randomized User Study for Physical Activity Recommender SystemsAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664867(176-182)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3631700.3664867
Park RPande ARelyea DChennu PKanmanth Reddy PHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)SLH-BIA: Short-Long Hawkes Process for Buy It Again Recommendations at ScaleProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3661374(2965-2969)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3661374
Dai SQu CChen SZhang XXu JHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)ReCODE: Modeling Repeat Consumption with Neural ODEProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657936(2599-2603)Online publication date: 11-Jul-2024
https://doi.org/10.1145/3626772.3657936
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