A Recommender System of Extended Reality Experiences

PubDate: February 2020

Teams: Swinburne University of Technology

Writers: Irene Gironacci, Kim Vincs, John McCormick

PDF: A Recommender System of Extended Reality Experiences

Abstract

Interest in Extended Reality (XR) technologies - such as virtual, augmented, and mixed reality - has increased, due to the opportunities offered by such technologies to provide users with live immersive digital experiences. In particular, these technologies for simulations have been widely used in recent years in entertainment and training industries, but have often been limited by the predictability of the simulation, and the lack of personalization in terms of simulation suggestions. This project proposes an Extended Reality simulator that uses Artificial Intelligence to suggest Extended Reality experiences (or scenarios) to users, through a collaborative filtering approach.

This paper gives an overview of the extended reality simulators currently available, as well as the challenges involved, and describes how the proposed system resolves those challenges. It then illustrates the components of the developed software platform and investigates a collaborative filtering item-based recommendation system as a possible approach to propose Extended Reality experiences. The usage of this simulator for professional training can be highly valuable: the simulator will recommend personalized extended reality training experiences to the user, facilitating the learning of new skills.