AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation

• URL: http://arxiv.org/abs/2307.05469v1
• Date: Fri, 7 Jul 2023 06:48:58 GMT
• Title: AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation
• Authors: Jaeheyoung Jeon, Jung Hyun Ryu, Jewoong Cho, Myungjoo Kang
• Abstract summary: This paper presents a solution to the challenges faced by contrastive learning in sequential recommendation systems. It addresses the issue of false negative, which limits the effectiveness of recommendation algorithms.
• Score: 0.7883397954991659
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents a solution to the challenges faced by contrastive learning in sequential recommendation systems. In particular, it addresses the issue of false negative, which limits the effectiveness of recommendation algorithms. By introducing an advanced approach to contrastive learning, the proposed method improves the quality of item embeddings and mitigates the problem of falsely categorizing similar instances as dissimilar. Experimental results demonstrate performance enhancements compared to existing systems. The flexibility and applicability of the proposed approach across various recommendation scenarios further highlight its value in enhancing sequential recommendation systems.

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