Matrix Factorization Techniques for Recommender Systems
Yahoo (United States) · AT&T (United States)
Indexed incrossref
Abstract
As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels.
Citation impact
11,617
total citations
- FWCI
- 314.38
- Percentile
- 100%
- References
- 12
Citations per year
Authors
3Topics & keywords
Topics
Keywords
- Recommender system
- Computer science
- Matrix decomposition
- Factorization
- Product (mathematics)
- Matrix (chemical analysis)
- Non-negative matrix factorization
- Artificial intelligence
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