Movie Recommendation System
Implementation of movie recommendation system using Collaborative Filtering Technique using C language.
- Creation of utility matrix of ratings between users and movies.
- Finding similarity of new user (or concerned user) with other users using Centered Cosine Similarity (Pearson’s Correlation).
- Clustering of users based on similarity using k means clustering.
- Prediction of movies using Collaborative Filtering technique (Low Rank Matrix Factorization) based on clusters obtained in step 3.
- Top 10 movies printed on command line.
Instructions to run this system:
- Open recommender.c and correct all the paths. (on line 20,55,56,57 and 63).
- Open ui.c and correct all the paths. (on line 15, 41, 64, 67, 68).
- Open command line and locate the directory where source code is stored and type:
gcc ui.c kmeans.c matrix_normalization.c pearsons.c predictions.c recommender.c sorting.c utility_matrix.c
aon command line to execute the program.