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AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation

arXiv 2307.05469 ↗First posted 7 Jul 2023cs.IR cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 20 references that are in the map. First posted on arXiv 7 Jul 2023.

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17 of 20 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
  3. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  4. 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,173
  5. 2020Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hyperspherecited by 1,405
  6. 2018Self-Attentive Sequential Recommendationcited by 1,184
  7. 2017Neural Collaborative Filteringcited by 1,111
  8. 2019BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformercited by 964
  9. 2015Image-based Recommendations on Styles and Substitutescited by 706
  10. 2020Keystroke Dynamics as Part of Lifeloggingcited by 334
  11. 2020S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximizationcited by 311
  12. 2022DiffCSE: Difference-based Contrastive Learning for Sentence Embeddingscited by 132
5 more
  1. 2021Contrastive Learning for Representation Degeneration Problem in Sequential Recommendationcited by 121
  2. 2021Equivariant Contrastive Learningcited by 66
  3. 2022Improved Universal Sentence Embeddings with Prompt-based Contrastive Learning and Energy-based Learningcited by 30
  4. 2022InfoCSE: Information-aggregated Contrastive Learning of Sentence Embeddingscited by 26
  5. 2020Self-supervised Learning for Large-scale Item Recommendationscited by 11

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