Knowledge-based adaptation of XR user interfaces for stock market data visualization

Adaptation of Extended Reality (XR) interfaces to fit user needs and preferences presents a significant challenge. The available XR application development tools often require advanced programming skills, forming a barrier for non-specialists in XR technology and 3D modeling. The main contribution of this paper is a knowledge-based method for the adaptation of XR user interfaces, with a focus on the usage of semantic representation of the users’ profiles to tailor individual experiences within an XR environment to the users’ requirements. The primary aim is to optimize user satisfaction and performance by enabling the adaptation of XR content by non-IT specialists using common or domain knowledge. As a case study for utilizing user profile-based adaptation, the paper presents an adaptive XR stock exchange data visualization system.