Mealionaire: A context-aware and ontology-based mobile recommender system for...Carter Chen
The night markets and the small eats in Taiwan are famous all over the world, eating is the big thing in Taiwan. No matter what time is it, people here in Taiwan can go outdoors, accessing vendors and get something to eat. Although those food vendors and restaurants provide a great variety of fresh food for people to choose, people have a hard time to make decisions sometimes. In this study, we have proposed a mobile recommender system, which is called Mealionaire. The recommender system is context-aware, which means it can perceive the context around the user and the recommendations it produced will adapt to the context whenever the context changes. In addition, it also introduces ontology technologies to analyze the relations between the user, the restaurants and the dishes which are served by the restaurants, in order to provide tailored, personalized results for the user in real-time fashion. The evaluation results show that Mealionaire can provide high user satisfaction, and it is capable to solve the problems that users may face when they are looking for appropriate dishes to eat in their daily lives.
