About on Project: This graduation project focuses on implementing and evaluating three popular recommendation algorithms: K-Nearest Neighbor (KNN), Apriori, and Collaborative Filtering. These algorithms help users find relevant items based on their preferences, increasing customer satisfaction. KNN provides personalized recommendations by finding the closest item to the user based on their choices. Apriori identifies frequently occurring items for targeted discounts or promotions. Collaborative Filtering ranks items based on the preferences of similar users, offering high-ranking recommendations.
My role: I Developed a Collaborative Filtering algorithm so that it can study the behavior of the user and evaluate the products based on his behavior, a similarity is found between the products that the user liked, and through that, some products are recommended to the user.