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cs.IR2025
Multi-Granularity Sequence Denoising with Weakly Supervised Signal for Sequential Recommendation
Liang Li, Zhou Yang, Xiaofei Zhu
Sequential recommendation aims to predict the next item based on user interests in historical interaction sequences. Historical interaction sequences often contain irrelevant noisy…
cs.IR2024
Multi-Level Sequence Denoising with Cross-Signal Contrastive Learning for Sequential Recommendation
Xiaofei Zhu, Liang Li, Weidong Liu +1
Sequential recommender systems (SRSs) aim to suggest next item for a user based on her historical interaction sequences. Recently, many research efforts have been devoted to attenu…