A collaborative filtering based recommendation engine and NPM module built on top of Node.js and Redis. The engine uses the Jaccard coefficient to determine the similarity between users and k-nearest-neighbors to create recommendations. This module is useful for any with a database of users, a database of products/movies/items and the desire to give their users the ability to like/dislike and receive recommendations.
Also I'm debating switching it to use the Neo4j graph database to take advantage of the traversal abilities, breadthe/depth in finding recommendations and time complexity.
- Node.js 0.10.x
- Redis
- Async
- Underscore
npm install racooon- Helper functions to pull in user data
- Change of data structure to an array of objects
- Implementation of Redis
- Helper functions to add new reviews
After installing Raccoon you should configure it.
- Code: 'git clone git://github.com/guymorita/raccoon.git'