Research map / Probabilistic and scientific modeling / Molecules and proteins
A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add side information via collective factorization (CMF vs PMF) | matrix factorization · Book-Crossing 80% | RMSE: 1.2453 -> 1.0563 | Helped |
| learn side-information latent factors with aSDAE jointly with MF | MF-based CF · MovieLens-1M 80% | RMSE: 0.5435 -> 0.5236 | Helped |
| aSDAE hybrid vs DCF | deep hybrid CF · MovieLens-100K 80% | RMSE: 0.5516 -> 0.5435 | Helped |
| aSDAE hybrid vs CDL/DCF | deep hybrid CF · MovieLens-100K, 1M, Book-Crossing | recall@K | Helped |
Closest papers by meaning
- Towards Faster Deep Collaborative Filtering via Hierarchical Decision Networks (AAAI 2021 · similarity 0.90)
- Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach (ICML 2021 · similarity 0.90)
- Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization (ICML 2025 · similarity 0.88)
- Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach (AAAI 2025 · similarity 0.87)
- DR-VAE: Debiased and Representation-enhanced Variational Autoencoder for Collaborative Recommendation (AAAI 2025 · similarity 0.87)
- FACE: A General Framework for Mapping Collaborative Filtering Embeddings into LLM Tokens (NeurIPS 2025 · similarity 0.86)
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