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November 21, 2025ACM Transactions on Information Systems

Rethinking Convolutional Neural Network in Multimodal Sequential Recommendation

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Authors

ZZZhicheng ZhouXMXiangwu MengYZYujie Zhang

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Overview

Analysis shows an effective convolutional neural network improves multimodal recommendations, addressing user interaction challenges.

Key Points

  • PCMSRec architecture enhances multimodal sequential recommendation with advanced convolutional layers.
  • A novel convolutional neural network design supports long-range dependency modeling in user interaction sequences.
  • Experiments verified significant improvement over prior multimodal recommendation methods using five public datasets.
  • Findings highlight the potential of flexible architecture in tackling multimodal feature integration challenges.

Cite This Study

Zhou et al. (2025) studied this question.

synapsesocial.com/papers/6924e3ecc0ce034ddc34ed68https://doi.org/10.1145/3777377
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