METHOD FOR PROVIDING PERSONALIZED RECIPE RECOMMENDATIONS

Abstract

ABSTRACT A method (100) for providing personalized recipe recommendations. Further, the method comprising receiving user input including dietary preferences, ingredient availability, and uploaded images of food items. Further, the method (100) comprising the steps of processing the uploaded images using a convolutional neural network (CNN) to identify and classify ingredients. Further, the method (100) comprising the steps of querying a recipe database to retrieve recipes based on recognized ingredients and user dietary restrictions. Further, the method (100) comprising the steps of generating personalized recipe recommendations using a natural language processing (NLP) model. Further, the method (100) comprising the steps of displaying the recommendations to the user along with detailed cooking instructions and nutritional information. <>

Specification

Description:FIELD OF THE DISCLOSURE
[0001] This invention generally relates to the field of personalized recipe recommendation systems and, in particular, to a method for generating tailored culinary suggestions based on user inputs and image recognition technology to enhance user experience and dietary adherence.
BACKGROUND
[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] The increasing interest in healthy eating and dietary management has led to a demand for personalized recipe recommendations that cater to individual preferences an , Claims:1. A method (100) for providing personalized recipe recommendations, the method comprising the steps of:
receiving user input including dietary preferences, ingredient availability, and uploaded images of food items;
processing the uploaded images using a convolutional neural network (CNN) to identify and classify ingredients;
querying a recipe database to retrieve recipes based on recognized ingredients and user dietary restrictions;
generating personalized recipe recommendations using a natural language processing (NLP) model; and
displaying the recommendations to the user along with detailed cooking instructions and nutritional information.

2. The method (100) as claimed in claim 1, further comprising the step of receiving user feedback on the recommended recipes to refine future recipe suggestions and enhance the personalization algorithm based on user interactions.

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