Personalized Augmented Reality Based Tourism System: Big Data and User Demographic Contexts

A lack of required data resources is one the challenges accepting Augmented Reality (AR) to provide right services users, whereas amount spatial information produced by people increasing daily. This research aims design a personalized AR that based on tourist system retrieves big according users’ demographic contexts in order enrich source tourism. conducted two main steps. First, type attraction where users interest predicted user contexts, which include age, gender, and education level, using machine learning method. Second, correct for are extracted from considering time, distance, popularity, neighborhood places, VIKOR SWAR decision making methods. By about 6%, results show better performance tree predicting attraction, when compared SVM In addition, study overall satisfaction participants terms ease-of-use, 55%, systems usefulness, 56%.