Dual-grained global graph neural network for session-based recommendation

Jiang Zongli; Siheng Zhao

doi:10.1117/12.2681599

1 June 2023 Dual-grained global graph neural network for session-based recommendation

Jiang Zongli, Siheng Zhao

Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 127181A (2023) https://doi.org/10.1117/12.2681599
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China

Abstract

The session-based recommendation (SBR) is a task to predict user next action based on anonymous behavior sequences. Most existing studies utilize global context in conjunction with current session information to improve recommendation results. However, the local and global perspectives have an inherent conflict, and it has been a great challenge to integrate the two types of information. In this paper, we propose a novel recommendation method, namely, dual-grained global graph neural network (DG-GNN), to capture collaborative information from all sessions in a more subtle manner to model current user preferences. Specifically, we convert the local and global content into two graphs and process them with the corresponding encoders. The local section exploits the graph attention network to learn a set of item-level embeddings. The global section collects the pairwise item transitions relevant to the current session for constructing graphs and exploits a lightweight encoder to learn a single session-level embedding, which reduces the influence of irrelevant information from global content on the local section. Moreover, a new position embedding mechanism is proposed to generate different position embeddings depending on the length of sessions for enhancing the ability to capture position information. Experiments on real-world datasets demonstrate that DG-GNN outperforms other state-of-the-art methods.

Citation Download Citation

Jiang Zongli and Siheng Zhao "Dual-grained global graph neural network for session-based recommendation", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 127181A (1 June 2023); https://doi.org/10.1117/12.2681599

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