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A Sequential Recommendation Model Based on Convolutional Neural Networks and State Space Models

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Novel CNN-Mamba model enhances recommendation accuracy by integrating short- and long-term preferences.

The CNN-Mamba model significantly enhances recommendation accuracy and efficiency.
Integration of CNN for short-term interests and SSM for long-term preferences shows promising results.
Adaptive fusion layer improves model generalization across varied user behavior sequences.
Experimental validation on real-world datasets showcases its superiority over traditional methods.

Feng et al. (2025) studied this question.

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View Full Paper

Ask AI

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Authors

Novel CNN-Mamba model enhances recommendation accuracy by integrating short- and long-term preferences.

The CNN-Mamba model significantly enhances recommendation accuracy and efficiency.
Integration of CNN for short-term interests and SSM for long-term preferences shows promising results.
Adaptive fusion layer improves model generalization across varied user behavior sequences.
Experimental validation on real-world datasets showcases its superiority over traditional methods.

Feng et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark