User-Based and Item-Based Collaborative Filtering
Implementation of user-based and item-based collaborative filtering algorithms using the MovieLens dataset. The data is stored in a ga.mat file containing a MATLAB struct structure where ga.train represents the training set and ga.test represents the test set. The original MovieLens dataset, which comes pre-divided into training and testing subsets, has been consolidated into this single ga.mat file for convenience. Both collaborative filtering approaches require pre-computation of similarity distances between items or users, which is performed offline and stored in .mat files for efficiency.