Recipe-Fusion: Multimodal Food Recipe Recommendation System

Year : 2024 | Volume :11 | Issue : 03 | Page : –
By

Karthik Anilkumar Nair,

Sanjog Gajanan Chavhan,

Tejas Nilkanth Pawar,

Anmol Jagdish Reddy,

K.S. Charumathi,

  1. Student, Department of Computer Engineering, Pillai College of Engineering, New Panvel, Maharashtra, India
  2. Student, Department of Computer Engineering, Pillai College of Engineering, New Panvel, Maharashtra, India
  3. Student, Department of Computer Engineering, Pillai College of Engineering, New Panvel, Maharashtra, India
  4. Student, Department of Computer Engineering, Pillai College of Engineering, New Panvel, Maharashtra, India
  5. Professor, Department of Computer Engineering, Pillai College of Engineering, New Panvel, Maharashtra, India

Abstract

The food recipe recommendation system using data science is a software solution designed to help users discover new and delicious food options based on their food history and other relevant data. This system recommends various recipes based on the input given by the user and it helps to filter out the recipes on course type, diet type, and nature of the food (including non-veg, and veg) using a recommendation technique. The system also analyzes food trends and popular dishes that the users might not have considered before. The system can recognize the input ingredients provided by the user and give the recipe based on the ingredients mentioned. Various machine learning and deep learning approaches like CNN and RNN will be used for the implementation of this system. The CNN model is trained and implemented to recommend the recipes based on the image similarity score. The RNN model is trained and implemented for prediction of the recipes from the input (recipe name) given by the user. Both models (CNN and RNN) are used simultaneously for the implementation of the system, which is why it is named as “Multimodal Food Recipe Recommendation System”. This system will help the person learn and make recipes based on the input given to it. This system will simplify finding relevant recipes for the user.

Keywords: Recommendation, Content-based, Machine learning, Deep learning approaches, convolutional neural network

[This article belongs to Journal of Artificial Intelligence Research & Advances (joaira)]

How to cite this article:
Karthik Anilkumar Nair, Sanjog Gajanan Chavhan, Tejas Nilkanth Pawar, Anmol Jagdish Reddy, K.S. Charumathi. Recipe-Fusion: Multimodal Food Recipe Recommendation System. Journal of Artificial Intelligence Research & Advances. 2024; 11(03):-.
How to cite this URL:
Karthik Anilkumar Nair, Sanjog Gajanan Chavhan, Tejas Nilkanth Pawar, Anmol Jagdish Reddy, K.S. Charumathi. Recipe-Fusion: Multimodal Food Recipe Recommendation System. Journal of Artificial Intelligence Research & Advances. 2024; 11(03):-. Available from: https://journals.stmjournals.com/joaira/article=2024/view=171716



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Regular Issue Subscription Review Article
Volume 11
Issue 03
Received June 28, 2024
Accepted August 21, 2024
Published September 11, 2024
Views: 28

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