Matrix Factorization Techniques for Recommender Systems.¶
Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix Factorization Techniques for Recommender Systems. Computer, 42(8), 30-37.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Factorization
- Matrix factorization moved into recommender systems as the "users and items in a shared latent space" pattern now standard in collaborative filtering and embedding-based retrieval.
This sourceCanonical statement of matrix factorization placing users and items in a shared latent-factor space, the structure carried from numerical algebra into collaborative filtering.
- Matrix factorization moved into recommender systems as the "users and items in a shared latent space" pattern now standard in collaborative filtering and embedding-based retrieval.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Not recorded. The single citation of this work carries no recorded support check.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Registry ID ref:7665917deb30 · see in the full table