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TSESRec: A transformer-facilitated set extension model for session-based recommendation

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Abstract

Session-based recommendation presents a challenging task, aimed at recommending subsequent items based on anonymous behavioral sequences. The current session-based recommendation methods heavily rely on the order of interactions. However, we observed that the interaction order within a session might not be reliable because interactions often contain noise, such as unintentional or erroneous interactions. In such cases, overemphasizing the order can interfere with the recommendation results. This paper proposes a new hypothesis regarding the relationship between interaction order and recommendation results, suggesting that observed historical interactions constitute unordered feature data, and the order of interactions does not affect session recommendation outcomes. To validate the aforementioned hypothesis, we represent sessions in the form of sets and propose a Transformer-facilitated set extension model for session-based recommendation (TSESRec). We validated the effectiveness of the above hypothesis through comparative experiments on the TSESRec model. The model performed well compared to other advanced baselines, outperforming all baselines on specific-length datasets, indicating its advantages for session-based recommendations.

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No datasets were generated or analyzed during the current study.

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Acknowledgements

This work was supported by the National Social Science Fund of China (No. 22CGL050) and National Natural Science Foundation of China (NSFC72234004). The financial support is gratefully acknowledged.

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Authors and Affiliations

  1. Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Chen Liu, Tianhao Yu, Lixin Zhou & Xiaoyu Gong

  2. School of Economics and Management, Tongji University, Shanghai, 200091, China

    Xianghong Zhou

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  1. Chen Liu
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  2. Tianhao Yu
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  3. Xianghong Zhou
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  4. Lixin Zhou
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  5. Xiaoyu Gong
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Contributions

C.L. performed methodology, validation, and writing—review and editing. T.Y. presented methodology, validation, and writing—original draft. X.Z. provided validation and writing—review and editing. L.Z. carried out methodology, writing—original draft, and writing—review and editing. X.G. conducted validation and writing—review and Editing.

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Correspondence to Xianghong Zhou or Lixin Zhou.

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Liu, C., Yu, T., Zhou, X. et al. TSESRec: A transformer-facilitated set extension model for session-based recommendation. J Supercomput 81, 304 (2025). https://doi.org/10.1007/s11227-024-06814-2

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