An Introduction to Matrix factorization and Factorization Machines in Recommendation System, and Beyond

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D. Billsus, M. J. Pazzani et al. , “Learning collaborative information filters.” in Icml , vol. 98, 1998, pp. 46–54
1998
Earlier work this paper cites.
G. Linden, B. Smith, and J. York, “Amazon. com recommendations: Item-to-item collaborative filtering,” IEEE Internet computing , vol. 7, no. 1, pp. 76–80, 2003
2003
Earlier work this paper cites.
S. Funk, 2006. [Online]. Available: http://sifter.org/~simon/journal/20061211.html
2006
Earlier work this paper cites.

Y. Koren, “Factor in the neighbors: Scalable and accurate collaborative filtering,” ACM Transactions on Knowledge Discovery from Data (TKDD) , vol. 4, no. 1, pp. 1–24, 2010
2010
Cited alongside, same era.
S. Rendle, “Factorization machines,” in 2010 IEEE International Conference on Data Mining , 2010, pp. 995–1000
2010
Cited alongside, same era.
[Online]. Available: https://www.cnblogs.com/pinard/p/6251584.html
Cited in the paper.
[Online]. Available: https://web.stanford.edu/class/cs168/l/l9.pdf
Cited in the paper.
[Online]. Available: https://github.com/microsoft/recommenders/blob/master/notebooks/02_model/fm_deep_dive.ipynb
Cited in the paper.
[Online]. Available: https://zhuanlan.zhihu.com/p/25836678
Cited in the paper.
[Online]. Available: https://zhuanlan.zhihu.com/p/32230623
Cited in the paper.

Y. Juan, D. Lefortier, and O. Chapelle, “Field-aware factorization machines in a real-world online advertising system,” in Proceedings of the 26th International Conference on World Wide Web Companion , 2017, pp. 680–688
2017
Later among the works it cites.
R. Wang, B. Fu, G. Fu, and M. Wang, “Deep & cross network for ad click predictions,” in Proceedings of the ADKDD’17 , 2017, pp. 1–7
2017
Later among the works it cites.