Sparse multimodal embeddings boost cold-start recommendation accuracy
_reachsumit · x · 2026-07-21
## Sparse multimodal embeddings improve cold-start recommendation This paper proposes **sparse multimodal embeddings** for content-based cold-item recommendation. - The method combines multimodal content signals with sparse representations. - It is designed for **cold-start** recommendation where interaction history is limited. - The authors report large accuracy gains over dense embedding baselines.
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