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Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation

Research article (Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022) · cited 396× · AI/ML
academia openalex:W3206127589
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Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation

Summary

Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation is a scholarly article[1].

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  • Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation's instance of is recorded as scholarly article[2].

Related Entities

Zi Huang

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. Retrieved May 24, 2026, from https://4ort.xyz/entity/contrastive-learning-for-representation-degeneration-problem-in-sequential-recommendation
MLA “Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/contrastive-learning-for-representation-degeneration-problem-in-sequential-recommendation.
BibTeX @misc{4ortxyz_contrastive-learning-for-representation-degeneration-problem-in-sequential-recommendation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation}}, year = {2026}, url = {https://4ort.xyz/entity/contrastive-learning-for-representation-degeneration-problem-in-sequential-recommendation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation — https://4ort.xyz/entity/contrastive-learning-for-representation-degeneration-problem-in-sequential-recommendation (retrieved 2026-05-24)

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