This is a demo of a content-based filtering recommendation engine built in ruby. The engine recommends board games based on the user's profile. The algorithm uses four game features to calculate a similarity score of between 0 - 100 for each game. A similarity score is a measure of the closeness or likeness of a game to the user's preferences. The similarity score is then used to recommend games the user might love.
- Update user's profile when they review new games