Intelligent Food Recipes Recommendation System
Student: Tarila Sharon Yinkere (Project, 2025)
Department of Computer Science
University of Port-Harcourt, Rivers State
Abstract
The project focuses on developing an Intelligent Food Recipes Recommendation System, aimed at assisting users in discovering new recipes based on their preferences, dietary restrictions, and available ingredients. The system utilizes a combination of machine learning algorithms, Object-Oriented System Analysis and Design Methodology (OOSADM), and collaborative filtering techniques to analyze user input and suggest personalized recipes. Using Object-Oriented System Analysis and Design (OOSAD) methodology, the system architecture is carefully crafted to support modularity, reusability and scalability. The collaborative filtering approach enables the system to analyze user preferences and behaviors, using data from similar users to recommend recipes that align with individual tastes and dietary requirements. Python serves as the primary programming language, chosen for its versatility and rich ecosystem of libraries suitable for data processing, machine learning, and recommendation system development. This recommendation system aims to enhance user satisfaction by delivering relevant recipes, with potential applications in personalized nutrition, meal planning, and culinary exploration.
Keywords
For the full publication, please contact the author directly at: sharonyinkere@gmail.com
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Institutions
- University of Ilorin, Kwara State 402
- University of Jos, Jos, Plateau State 19
- University of Lagos 18
- University of Maiduguri ( - Elearning), Maiduguri, Borno State 3
- University of Maiduguri, Borno State 109
- University of Nigeria, Nsukka, Enugu State 270
- University of Port Harcourt Teaching Hospital, Port Harcourt , River State 6
- University of Port-Harcourt, Rivers State 175
- University of Uyo, Akwa Ibom State 207
- Usmanu Danfodio University, Sokoto, Sokoto State 245