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AI-Powered Recipe Recommendation Systems and Their Role in Personalized Nutrition

AI-Powered Recipe Recommendation Systems and Their Role in Personalized Nutrition
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Author(s): Vikas Sharma (Swami Vivekanand Subharti University, Meerut, India)and Nitin Gupta (Swami Vivekanand Subharti University, Meerut, India)
Copyright: 2026
Pages: 24
Source title: AI and the Future of Smart Cooking
Source Author(s)/Editor(s): Ankit Shukla (Rajamangala University of Technology, Thanyaburi, Thailand), Nagendra Yadav (Welcomgroup Graduate School of Hotel Administration, Manipal Academy of Higher Education, Manipal, India), Partho Pratim Seal (Manipal Academy of Higher Education, India)and Abhishek Tiwari (Burapha University International College, Thailand)
DOI: 10.4018/979-8-3373-4042-5.ch010

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Abstract

Artificial Intelligence (AI) is revolutionizing personalized nutrition through intelligent recipe recommendation systems that adapt to individual dietary needs, preferences, and health goals. These systems utilize machine learning algorithms, natural language processing, and user-generated data to curate meal suggestions that align with personal health profiles, such as allergies, fitness objectives, medical conditions, or cultural preferences. By analyzing nutritional content, consumption patterns, and user feedback, AI-driven platforms enhance user engagement and foster healthier eating habits. Moreover, integration with wearable devices and health apps allows for real-time dietary tracking and adaptive recommendations. Despite promising outcomes, challenges such as data privacy, algorithm transparency, and user trust remain critical. This paper explores the mechanisms, benefits, and limitations of AI-powered recipe recommendation systems and emphasizes their potential to transform modern dietary practices into personalized, data-driven nutrition models.

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