/Recommendation-System

Food Recommendation System based on three model of recommendations

Primary LanguageCSS

Food Recommendation System

A Restaurant and Dish Recommender system using user profile, order history and ratings based similarity computation.

The users are presented with a choice of three recommendation models. The first one is a content-based filtering model, whereas the second and third are keyword-based filtering models. In the third model, recommendations are modified based on user feedback.

Tech Stack

Frontend: Javascript, HTML, CSS

Backend: Python , Django , MySQL / Postgres SQL

others scikit-learn , numpy , pandas

Overview :

  • Utilizing person preference to recommend more personalized food items.

  • Content based recommendation system recommends items based on the content of items. I.e. features of items

  • First model is based on using TF-IDF vectorization and cosine similarity.

  • Second model is based on the keyword extracted from dishes like ingredients, flavor, profile etc.

  • Third model is based on penalization of keywords and promotion and demotion of certain keywords by feature vectors of the user based on the feedback received from users.