## 3、PMF

Salakhutdinov et al. Probabilistic matrix factorization. NIPS(2008): 1257-1264.

PMF是對於FunkSVD的概率解釋版本，它假設評分矩陣中的元素  是由使用者潛在偏好向量  和物品潛在屬性向量  的內積決定的，並且服從均值為  ，方差為  的正態分佈：

## 4、BiasSVD

Koren et al. Matrix factorization techniques for recommender systems.Computer 42.8 (2009).

## 5、SVD++

Koren Y. Factor in the neighbors: Scalable and accurate collaborative filtering[J]. ACM Transactions on Knowledge Discovery from Data (TKDD), 2010, 4(1): 1.

## 6、timeSVD

Koren et al. Collaborative filtering with temporal dynamics. Communications of the ACM 53.4 (2010): 89-97.

## 7、NMF

Lee et al. Learning the parts of objects by non-negative matrix factorization. Nature 401.6755 (1999): 788.

## 8、WMF

Pan et al. One-class collaborative filtering. ICDM, 2008.
Hu et al. Collaborative filtering for implicit feedback datasets. ICDM, 2008.

## 10、LLORMA

Lee et al. Local low-rank matrix approximation.ICML. 2013.

## 11、SRui

Ma Hao. An experimental study on implicit social recommendation. SIGIR, 2013.

## 12、ConvMF

Kim et al. Convolutional matrix factorization for document context-aware recommendation. RecSys 2016.

## 13、NCRPD-MF

Hu et al. Your neighbors affect your ratings: on geographical neighborhood influence to rating prediction. SIGIR 2014.