RETRACTED: An ontology-driven personalized food recommendation in IoT-based healthcare system (Retracted article. See vol. 79, pg. 5847, 2023)

The recent developments of internet technology have created premium space for recommender system (RS) to help users in their daily life. An effective personalized recommendation of a travel recommender system can reduce time and travel cost of the travellers. ProTrip RS addresses the personalization problem through exploiting user interests and preferences to generate suggestions. Data considered for the recommendations include travel sequence, actions, motivations, opinions and demographic information of the user. ProTrip is completely designed to be intelligent and in addition, the ProTrip is a health-centric RS which is capable of suggesting the food availability through considering climate attributes based on user's personal choice and nutritive value. A novel functionality of ProTrip supports travellers with long-term diseases and followers of strict diet. The ProTrip is built on the pillars of ontological knowledge base and tailored filtering mechanisms. The gap between heterogeneous user profiles and descriptions is bridged using semantic ontologies. The effectiveness of recommendations is enhanced through a hybrid model of blended filtering approaches, and results prove that the proposed ProTrip to be a proficient system. The developed food recommendation approach is evaluated for the real-time IoT-based healthcare support system. We also present a detailed case study on the food recommendation-based health management. The proposed system is evaluated on real-time dataset, and analysis of the results shows improved accuracy and efficiency compared to existing models.