Recipe Recommendation System Using TF-IDF
Shubham Chhipa, Vishal Berwal, Tushar Hirapure, Soumi Banerjee
Abstract
A Recipe Recommendation System is being proposed in this following paper. Food recommendation is a new area, with few systems that are focus on analysing and user preferences and constraints such as ingredients available at their side being deployed in real settings in the form of web application or mobile application [4]. The proposed model is a mobile application which allows users to search recipes using ingredients available at them including vegetables. For this work we have find a dataset which is a collection of Indian cuisines recipes and apply the content-based recommendation using Term Frequency – Inverse Document Frequency (TF-IDF) and Cosine Similarity [1]. This application gives the recommendation of Indian recipes based on ingredients available at them and allows users to filter out the recipes on course type, diet type, etc.