kev94yo / content-based-recommendation

Content based movie recommendation project

Content-based-recommendation

A content based recommendation program that performs item-item neighborhood collaborative filtering. This repo uses movie rating data to form a movie-user matrix and learn representations to recommend top N movies based on user id.

Requirements

Requirements can be found in requirements.txt

Datasets

Datasets are from the Movielens dataset

• Rating.csv: Ratings given to movies by users
• Movies_w_imgurl.csv: Movie metadata including genres
• Tags.csv: Tags given to movies by users

Recommendation Generation

In practice, adjust input.txt to change user ids to generate recommendations for

1. Adjust input.txt. The input format is user_id for each line
2. Run python main.py
3. Check output.txt for results. The output format is user_id, movie_id, prediction_score for each line. The result is sorted in descending order