https://github.com/rimo02/movie-recommendation

Recommending similar movies based on movie features/user ratings
https://github.com/rimo02/movie-recommendation

content-based-recommendation movie-recommendation

Last synced: 3 days ago
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Recommending similar movies based on movie features/user ratings

• Host: GitHub
• URL: https://github.com/rimo02/movie-recommendation
• Owner: rimo02
• Created: 2023-04-19T18:19:03.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-05-16T14:57:46.000Z (over 1 year ago)
• Last Synced: 2024-06-07T20:27:15.696Z (5 months ago)
• Topics: content-based-recommendation, movie-recommendation
• Language: Jupyter Notebook
• Homepage:
• Size: 14.2 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Collaborative filtering 

The Collaborative filtering method for recommender systems is a method that is solely based on the past interactions that have been recorded between users and items, in order to produce new recommendations. Collaborative Filtering tends to find what similar users would like and classify the similar users into clusters of similar types.

# Content-Based Filtering

The content-based approach uses additional information about users and/or items. This filtering method uses item features to recommend other items similar to what the user likes and also based on their previous actions or explicit feedback. If we consider the example for a movies recommender system, the additional information can be, the age, the movie genre that the user likes, the job or any other personal information for users as well as the category, the main actors, the duration or other characteristics for the movies i.e the items.