Session-based recommendation (SBR) systems, traditionally reliant on complex graph neural networks (GNNs), often face challenges with marginal performance improvements despite increased model complexity. In this paper, we dissect the classical GNN-based SBR models and empirically find that the sophisticated GNN propagations might be redundant, given the readout module plays a significant role in GNN-based models. Based on this observation, we introduce Atten-Mixer+, an advanced iteration of our previously developed Multi-Level Attention Mixture Network (Atten-Mixer). Atten-Mixer+ forgoes GNN propagation in favor of a dynamic and adaptive readout process, tailored to the unique characteristics of each session. Different from the vanilla version, Atten-Mixer+ features the Adaptive Intent Scaler (AIS) layer, which dynamically determines the depth of multi-level user intent analysis, and a soft allocation approach for generating user intent queries across entire user interaction sequences. This innovative design allows Atten-Mixer+ to capture a nuanced and comprehensive understanding of user behaviors, overcoming the limitations of fixed-length analysis. Empirical evaluations on benchmark datasets highlight Atten-Mixer+'s superior efficiency and effectiveness, marking a significant step forward in the predictive accuracy of session-based recommendation systems.

Peiyan Zhang

Jiayan Guo

Chaozhuo Li

Liying Kang

Jaeboum Kim

Jie Xu

Xi Zhang

Yan Zhang

Haohan Wang

Sunghun Kim

ACM Transactions on Intelligent Systems and Technology

ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 是一本学术期刊，以多学科的视角发表关于智能系统、适用算法和技术的最高质量论文。智能系统是使用人工智能 (AI) 技术提供重要服务（例如，作为更大系统的组件）以允许集成系统在现实世界中感知、推理、学习和智能行动的系统。ACM TIST 是每季出版（一年六期）。每期有 8-11 篇常规论文，大约有 20 个已发表的期刊页面或每篇论文 10,000 字。额外的参考文献、证明、图表或详细的实验结果可以作为单独的附录提交，而过长的论文将被自动拒绝。作者可以在其已发表论文的其他内容中包含仅在线附录，并鼓励与其他读者共享其代码和/或数据。

ACM Transactions on Intelligent Systems and Technology is an academic journal that publishes high-quality papers on intelligent systems, applicable algorithms, and technologies from a multidisciplinary perspective. Intelligent systems use artificial intelligence (AI) technologies to provide essential services, functioning as components of larger systems, enabling integrated systems to perceive, reason, learn, and act intelligently in the real world. ACM TIST is published quarterly, with six issues per year, each containing 8 to 11 regular papers, approximately 20 published journal pages, or up to 10,000 words per paper. Additional references, proofs, charts, or detailed experimental results may be submitted as separate appendices, and excessively long papers will be automatically rejected. Authors are allowed to include online-only appendices in their published papers and are encouraged to share their code and/or data with other readers.

《ACM Transactions on Intelligent Systems and Technology》是一本学术期刊，采用多学科的视角，发表关于智能系统、相关算法和技术的高质量论文。智能系统利用人工智能（AI）技术提供重要服务，作为更大系统的组成部分，使得集成系统能够在现实世界中进行感知、推理、学习和智能行动。该期刊每季度出版六期，每期包含8到11篇常规论文，约20页的已发表期刊内容，或每篇论文不超过10,000字。额外的参考文献、证明、图表或详细的实验结果可以作为附录提交，过长的论文将被自动拒绝。作者可以在已发表论文中包含仅在线附录，并鼓励与其他读者共享其代码和/或数据。

Category	Quartile
计算机科学	4
计算机科学, 计算机人工智能	4
计算机科学, 计算机信息系统	4

Advancing Session-Based Recommendations with Atten-Mixer+: Dynamic and Adaptive Multi-Level Intent Mining

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Journal Info

Category	Quartile
COMPUTER SCIENCE, INFORMATION SYSTEMS	1