https://github.com/arasraj/Recommender_System

CF item-based recommender system
https://github.com/arasraj/Recommender_System

Last synced: 11 days ago
JSON representation

CF item-based recommender system

• Host: GitHub
• URL: https://github.com/arasraj/Recommender_System
• Owner: arasraj
• Created: 2011-07-25T22:06:51.000Z (over 13 years ago)
• Default Branch: master
• Last Pushed: 2011-08-04T07:26:34.000Z (over 13 years ago)
• Last Synced: 2024-08-01T22:57:21.969Z (3 months ago)
• Language: Python
• Homepage:
• Size: 4.87 MB
• Stars: 28
• Watchers: 5
• Forks: 14
• Open Issues: 0
• Metadata Files:
  • Readme: README

Awesome Lists containing this project

README

        
This is a collaborative filtering item-based recommender system.  User ratings are on a 5-star

scale.  The item-item similarity matrix is computed using Adjusted Cosine similarity.  Most 

data structures are serialized to disk and loaded into memory when needed.  This is to avoid 

repeating computationaly heavy tasks. This code can be extended to recommend books on a per 

user basis pretty easily.  It can also be extending to provide predictions on what a user

would rate a specific book using a weighted knn approach.

To test:

> python generate.py test

NOTE: test_bookset.pkl, test_ratings.pkl, indextobook.pkl, booktoindex.pkl, usertoindex.pkl must be in the same working directory inorder for test() to work. All "pickled" objects are provided for testing only. If you have access to the correct mysql dataset these object are generated for you.

The visualization of item similarities is shown in bookrec.html.