Recommendation System with Association Rule Mining and Mobile Augmented Reality

Mobile augmented reality is a popular technology field that allows simultaneous interaction between the real world and the virtual world with the help of mobile devices. The notion of object recognition and classification, which plays an important role in mobile augmented reality applications, is the process of identifying an object on the image and assigning it to a certain class label. In this study, a novel three-dimensional and real time recommendation system has been developed with association rule mining and mobile augmented reality. The proposed system consists of three stages: (1) Recognition and classification of the object on the image (2) Determination of the related rules of the object with other objects in the dataset by using the Apriori algorithm (3) Adding recommendations that generated from the rules to the image as virtual objects with mobile augmented reality. Although the developed system in this study is a general recommendation system, it was applied in the field of market basket analysis as an experimental study.