Matrix Factorization-based Collaborative Filtering Algorithm

A Matrix Factorization-based Collaborative Filtering Algorithm is an model-based collaborative filtering algorithm that applies a matrix factorization algorithm.

• Context:
  • It can be implemented by a Matrix Factorization-based Recommendation System (to solve a matrix factorization-based recommendation task).
• Example(s):
  • one based on ALS Algorithm.
  • …
• Counter-Example(s):
  • a Deep Neural Network-based Recommendation Algorithm.
  • a k-Nearest Neighbor-based Item Recommendation Algorithm.
• See: Algorithm-Specific Task, RL-based Recommender Algorithm.

---

---

References

2019

• (Rendle et al., 2019) ⇒ Steffen Rendle, Li Zhang, and Yehuda Koren. (2019). “On the Difficulty of Evaluating Baselines: A Study on Recommender Systems.” In: arXiv preprint arXiv:1905.01395.
  • ABSTRACT: ... With a careful setup of a vanilla matrix factorization baseline, we are not only able to improve upon the reported results for this baseline but even outperform the reported results of any newly proposed method. ...

2012

• (Smola, 2012a) ⇒ Alex Smola. (2012). “Recommender Systems.” In: SML: Scalable Machine Learning - STATISTICS 241B, COMPUTER SCIENCE C281B
  • QUOTE: Singular value decomposition, Convex reformulation, ...

2010

• (Jamali & Ester, 2010) ⇒ Mohsen Jamali, and Martin Ester. (2010). “A Matrix Factorization Technique with Trust Propagation for Recommendation in Social Networks.” In: Proceedings of the fourth ACM conference on Recommender systems, pp. 135-142 . ACM,

2009

• (Koren et al., 2009) ⇒ Yehuda Koren, Robert Bell, and Chris Volinsky. (2009). “Matrix Factorization Techniques for Recommender Systems.” Computer 42, no. 8
  • QUOTE: 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.

2001

• (Lee & Seung, 2001) ⇒ Daniel D. Lee and H. Sebastian Seung. (2001). “Algorithms for Non-negative Matrix Factorization.” In: Advances in Neural Information Processing Systems 13: Proceedings of the 2000 Conference.

---