TME-PSR: Time-aware, Multi-interest, and Explanation Personalization for Sequential Recommendation

• URL: http://arxiv.org/abs/2604.09439v1
• Date: Fri, 10 Apr 2026 15:55:54 GMT
• Title: TME-PSR: Time-aware, Multi-interest, and Explanation Personalization for Sequential Recommendation
• Abstract summary: We propose a sequential recommendation model that integrates Time-aware personalization, Multi-interest personalization, and Explanation personalization for Personalized Sequential Recommendation (TME-PSR)<n>Our method consistently improves recommendation accuracy and explanation quality, at a lower computational cost.
• Score: 18.256420931120264
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose a sequential recommendation model that integrates Time-aware personalization, Multi-interest personalization, and Explanation personalization for Personalized Sequential Recommendation (TME-PSR). That is, we consider the differences across different users in temporal rhythm preference, multiple fine-grained latent interests, and the personalized semantic alignment between recommendations and explanations. Specifically, the proposed TME-PSR model employs a dual-view gated time encoder to capture personalized temporal rhythms, a lightweight multihead Linear Recurrent Unit architecture that enables fine-grained sub-interest modeling with improved efficiency, and a dynamic dual-branch mutual information weighting mechanism to achieve personalized alignment between recommendations and explanations. Extensive experiments on real-world datasets demonstrate that our method consistently improves recommendation accuracy and explanation quality, at a lower computational cost.

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