Search, retrieval & recommendation· 2017
Neural Collaborative Filtering
On the reading lists
- #157 in the Top 500 (2026 edition)
- #8 in Search, retrieval & recommendation (2026 edition)
Why it matters
Popularized neural user-item interaction modeling beyond conventional matrix-factorization dot products.
Condensed from the expert lists' notes.
The record
- First released
- 2017 (from arXiv 1708.05031)
- Citations
- 7,434 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.592 · computed rank 157 · consensus 0.64, must-read 0.5, citations percentile 1 (2010s · retrieval), awards 0, existing lists 0. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.