Use of Artificial Intelligence and Machine Learning for Personalization Improvement in Developed e-Material Formatting Application

Abstract

Although screen technology use in most daily tasks, including daily work tasks and educational reasons, a significant part of users and learners are having problems to read the more extended time without complains. Developed E-material formatting application is working based on the developed methodology for e-material formatting as an improvement for text perception from the screen. The methodology is limited and includes several variables for general formatting improvement and primary personalization. More in-depth and more specific personalization ask for a broader range of variables to be involved. That comes to an enormous number of potential configurations in total. It is not something that the human mind can operate and generate appropriate methodologies. Artificial Intelligence and Machine Learning use can improve personalization as can proses a huge amount of data and analyze algorithms faster to get a solution and reach the goal. Methodology: use case analysis of E-material formatting application. Results: Paper includes short description of current situation and developed application; description of existing application limitations and challenges; analysis for Artificial Intelligence and Machine Learning use in this case; analysis of necessary data for Machine Learning development; description of the information types Artificial Intelligence generates after learning process and description of the Artificial Intelligence process for e-material formatting personalization. Conclusions: Use of Artificial Intelligence and Machine Learning is reasonable for personalization improvement in developed E-material formatting application.