سيستم پيشنهاد‌دهنده غذا با رويكرد سلامت‌محور با استفاده از داده‌كاوي عادت‌هاي تغذيه‌اي كاربران

In the dynamic world of digital platforms, recommendation systems play a pivotal role in increasing user engagement through personalized content delivery. Given the significance of health and nutrition in the modern era, food recommendation systems have become the focus of researchers. The most important challenge in developing food recommendation systems is providing healthier food options, but it has been shown in numerous cases that adding this criterion negatively impacts the accuracy of the recommendations or eliminates many items from the recommendation algorithm. The primary goal of this research is to develop a recommendation system with suitable accuracy to provide personalized and healthy dietary recommendations to improve users’ eating habits. The use of advanced algorithms developed for recommendation systems, along with the utilization of features extracted through data mining, including the identification and separationofdifferentusercommunitiesandtheaccurateassessmentofusers’importance and attention to their health, can lead to improved performance of recommendation systems in the field of nutritional health. This process demonstrates that by adopting a suitable and intelligent approach, a system can be designed and implemented that, while maintaining accuracy and technical efficiency, is also capable of providing healthier and more optimized food recommendations. This system, by considering the individual needs and preferences of users, can provide an effective solution to encourage healthier food choices and consequently contribute to improving public health. The eva‎luation results in this research show that the selection of appropriate scenarios has been able to improve the health of the recommendations while maintaining the accuracy of the used algorithms, which is an effective step in the field of health and food recommendation systems.

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