Tca4rec: contrastive learning with popularity-aware asymmetric augmentation for robust sequential recommendation

Tca4rec: contrastive learning with popularity-aware asymmetric augmentation for robust sequential recommendation

Abstract Sequential recommender systems play a pivotal role in modern recommendation scenarios by capturing users’ dynamic interests through their historical interactions. While existing methods often rely on sophisticated deep models to enhance recommendation quality, they suffer from performance d...

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Bibliographic Details
Main Authors: Yanan Bai, Liji Xiao, Chongjun Xia, Kexiang Zeng, Xiaoyu Shi
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:Journal of Big Data
Subjects:
Sequential recommender system
Robust recommendation
Contrastive learning
Popularity bias
Data sparsity
Online Access:https://doi.org/10.1186/s40537-025-01184-9
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https://doi.org/10.1186/s40537-025-01184-9

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