YuanchenBei/Awesome-Cold-Start-Recommendation

This resource provides a comprehensive list of research papers and toolkits focused on 'cold-start recommendation'. This is a common challenge in recommendation systems where it's difficult to suggest relevant items to new users or suggest new items to existing users due to a lack of historical interaction data. It offers a structured overview of techniques and research trends, categorized by different aspects like content features, graph relations, and the use of Large Language Models. Anyone building or researching recommendation systems, from e-commerce product managers to streaming service data scientists, would find this useful for understanding and addressing this specific problem.

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