This project built for movie recommendation system based on collaborative filtering user based and item based recommendations.
Functions for recommendation written with MATLAB.
I used MovieLens dataset to train model.
Pearson correlation used for user based similarity and cosine similarity used for item based similarity.
For improving the efficieny, I used significance weighting.
I used 10fold to find best k values for each prediction method.
To take recommendation from website, firstly you should register and login the system.
After that, you must rate 20 movie to get prediction.
