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
- Landmark University, Omu-Aran, Kwara State 1
- Lead City University, Ibadan, Oyo State 1
- Lens Polytechnic, offa, Kwara State. 215
- Madonna University, Elele, Rivers State 20
- Madonna University, Okija, Anambra State 2
- Mcpherson University, Seriki Sotayo, Ogun State 1
- Michael and Cecilia Ibru University, Owhrode, Delta State 1
- Michael Okpara University of Agriculture, Umudike 43
- Michael Otedola Col of Primary Educ. Epe, Lagos (affl To University of Ibadan) 8
- Modibbo Adama University, Yola, Adamawa State 15