Papers with FCS

1 papers
Few-Shot Learning for Cold-Start Recommendation (2024.lrec-main)

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Challenge: Existing methods for cold-start learning and recommendation are brittle to scenarios with few interactions.
Approach: They propose a Few-shot learning method for Cold-Start recommendation that consists of three hierarchical structures that are local and global .
Outcome: The proposed method improves on two public real-world datasets and is stable compared with the state-of-the-art.

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