horse

Handy Open Recommendation Service

Frontend app url:

http://test-horse.s3-website-eu-west-1.amazonaws.com/

Backend app url:

http://horse-env.pqmnkwtbum.eu-west-1.elasticbeanstalk.com/

Frontend app repository:

https://github.com/pragmaticcoders/horse-frontend

Recommendation assumptions

• User movie recommendations are influenced by general movie popularity.
• Movies liked by followed users are more likely to be recommended. That relation is recursive, but with exponentialy decreasing power.
• Similarity score between any pair of users can be calculated. It is based on a count of commonly liked movies and is adjusted according to a total number of movies graded by both users.
• Movie recommendations are influenced by all points above.

Installation

Python 3.4 is required.

$ cd horse
$ pip install .
$ python application.py

Testing

$ tox

Populate with example dataset

$ curl -X POST http://127.0.0.1:5000/populate -d @./examples/populate.json --header "Content-Type: application/json"