research-article

Position-aware graph neural network for session-based recommendation

Authors:

Nan LiuAuthors Info & Claims

Volume 262, Issue C

https://doi.org/10.1016/j.knosys.2022.110201

Published: 28 February 2023 Publication History

Abstract

Session-based recommendations (SBRs) make recommendations using the current interaction sequence of users. Recent studies on SBRs have primarily used graph neural networks (GNNs) to model the session sequence; however, such methods treat the same items in a session as a single node, thus ignoring differences between items in different positions. Moreover, they do not use other sessions to learn users’ short-term preferences. Therefore, we propose a novel position-aware graph neural network (PA-GNN) for SBRs. First, this model uses a session in the form of a position-aware graph as an input to completely use the position information of the item and apply the attention mechanism to learn users’ long-term interests. Second, it combines other sessions to learn the user’s short-term preferences. Third, it integrates long-term interests and short-term preferences for predictions. The experimental results using three benchmark e-commerce datasets demonstrate that the PA-GNN model performs excellently and is superior to the latest baselines on SBRs.

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Cited By

Zhang WZhang JZhang Y(2024)A Comment Aspect-Level User Preference Transfer Model for Cross-Domain RecommendationsInformation Resources Management Journal10.4018/IRMJ.34536037:1(1-25)Online publication date: 17-Sep-2024
https://dl.acm.org/doi/10.4018/IRMJ.345360
Li FLiu HLi GWang YZhou HCao SLi T(2024)SeSMR: Secure and Efficient Session-based Multimedia Recommendation in Edge ComputingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/3687473Online publication date: 28-Aug-2024
https://doi.org/10.1145/3687473
Luo ZSheng ZZhang T(2024)Dual perspective denoising model for session-based recommendationExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123845249:PCOnline publication date: 17-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123845
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Index Terms

Position-aware graph neural network for session-based recommendation
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks
2. Information systems

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Published In

cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 262, Issue C

Feb 2023

472 pages

ISSN:0950-7051

Issue’s Table of Contents

Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 28 February 2023

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Cited By

Zhang WZhang JZhang Y(2024)A Comment Aspect-Level User Preference Transfer Model for Cross-Domain RecommendationsInformation Resources Management Journal10.4018/IRMJ.34536037:1(1-25)Online publication date: 17-Sep-2024
https://dl.acm.org/doi/10.4018/IRMJ.345360
Li FLiu HLi GWang YZhou HCao SLi T(2024)SeSMR: Secure and Efficient Session-based Multimedia Recommendation in Edge ComputingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/3687473Online publication date: 28-Aug-2024
https://doi.org/10.1145/3687473
Luo ZSheng ZZhang T(2024)Dual perspective denoising model for session-based recommendationExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123845249:PCOnline publication date: 17-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123845
Liu HLi FCheng H(2023)Secure Position-Aware Graph Neural Networks for Session-Based RecommendationArtificial Intelligence Security and Privacy10.1007/978-981-99-9788-6_11(134-146)Online publication date: 3-Dec-2023
https://dl.acm.org/doi/10.1007/978-981-99-9788-6_11

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