Description: [Turn] collaborative filtering code for the recommended system, including project-based and user-based two cases. User-based and project-based collaborative filtering algorithm. Experimental data for MovieLens- a web-based movies recommender system with 43,000 users & over 3500 movies. Saved in ga.mat file with Because ga.test test set is too large, all used to calculate the time-consuming massive, so every time The calculated random selection portion, the use of the specific function, please refer to probar.m. I obtained experimental results are saved inside results1-results8.mat.
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File list (Check if you may need any files):
Concha_CF\CF.m
.........\Collaborative_Filtering.pdf
.........\CollaFilter.m
.........\CollaFilterUser.m
.........\dibujar.m
.........\document.pdf
.........\ga.mat
.........\item based collaborative fiter.pdf
.........\ItemBasedCollaborativeFiltering_Sarvar.pdf
.........\probar.m
.........\readme.txt
.........\SimilitudItems.m
Concha_CF
.........\Concha_CF\CF.m
.........\.........\Collaborative_Filtering.pdf
.........\.........\CollaFilter.m
.........\.........\CollaFilterUser.m
.........\.........\dibujar.m
.........\.........\document.pdf
.........\.........\ga.mat
.........\.........\item based collaborative fiter.pdf
.........\.........\ItemBasedCollaborativeFiltering_Sarvar.pdf
.........\.........\probar.m
.........\.........\readme.txt
.........\.........\SimilitudItems.m
.........\Concha_CF
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