Users’ Rating Predictions Using Collaborating Filtering Based on Users and Items Similarity Measures

Table 6

Comparison of MF methods with Item-Item (Pearson Correlation) method.

Algorithms	RMSE			MAE
	ML	ML	Ciao DVD	ML	ML		Ciao DVD
	100k	1M		100k	1M
Matrix factorization	0.988	0.954	1.107	0.771	0.746		0.860
Biased matrix factorization	0.992	0.964	1.032	0.770	0.752		0.797
Factor wise matrix factorization	0.989	0.940	1.622	0.765	0.731		1.215
Item K-NN (Pearson correlation)	0.933	0.879	0.964	0.734	0.690		0.734