28 فروردین 1403

سجاد احمدیان

مرتبه علمی: استادیار
نشانی: دانشگاه صنعتی کرمانشاه
تحصیلات: دکترای تخصصی / مهندسی کامپیوتر
تلفن: 09188339565
دانشکده: دانشکده فناوری اطلاعات

مشخصات پژوهش

عنوان
A novel healthy and time-aware food recommender system using attributed community detection
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
Recommender System; Healthy Recommendation; Food recommendation; Community detection
پژوهشگران مهرداد رستمی (نفر اول)، وحید فرهی (نفر دوم)، سجاد احمدیان (نفر سوم)، سید محمد جعفر جلالی (نفر چهارم)، مراد اوصلاح (نفر پنجم)

چکیده

Food recommendation systems aim to provide recommendations according to a user’s diet, recipes, and preferences. These systems are deemed useful for assisting users in changing their eating habits towards a healthy diet that aligns with their preferences. Most previous food recommendation systems do not consider the health and nutrition of foods, which restricts their ability to generate healthy recommendations. This paper develops a novel health-aware food recommendation system that explicitly accounts for food ingredients, food categories, and the factor of time, predicting the user’s preference through time-aware collaborative filtering and a food ingredient content-based model. Based on the user's predicted preferences and the health factor of each food, our model provides final recommendations to the target user. The performance of our model was compared to several state-of-the-art recommender systems in terms of five distinct metrics: Precision, Recall, F1, AUC, and NDCG. Experimental analysis of datasets extracted from the websites Allrecipes.com and Food.com demonstrated that our proposed food recommender system performs well compared to previous food recommendation models.