Region-Based Indian Food Recommendation System

Abstract

In recent years, the popularity of Indian cuisine has grown significantly, both within India and across the globe. As a result, there is a growing demand for personalized food recommen dation systems that can suggest Indian dishes based on individual preferences. This Work presents a region-based Indian food recommendation system that utilizes a content-filtering algorithm to provide tailored recommendations. The proposed system considers the diverse culinary traditions across different regions of India, which offer distinct flavours, ingredients, meal times, and cooking techniques. The content filtering algorithm employed in this system analyzes a comprehensive database of Indian recipes, considering factors like ingredients, cooking methods, and regional affiliations. The experimental evaluation of the system demonstrates its effectiveness in providing personalized Indian food recommendations. The results indicate a high level of user satisfac tion and significantly improved recommendation accuracy compared to existing approaches. The region-based approach ensures that users can explore the culinary richness of various Indian cuisines, expanding their culinary horizons beyond their familiar choices. In conclusion, the proposed region-based Indian food recommendation system utilizing a content-filtering algorithm offers an innovative and personalized solution for suggesting Indian dishes based on individual preferences. It not only considers user-specific requirements but also takes into account the rich culinary diversity across different regions of India. The system has the potential to enhance the dining experience of users and promote cultural exploration through Indian cuisine.