1. bookVolume 26 (2021): Issue 1 (May 2021)
Journal Details
License
Format
Journal
First Published
08 Nov 2012
Publication timeframe
2 times per year
Languages
English
access type Open Access

Mapping of Source and Target Data for Application to Machine Learning Driven Discovery of IS Usability Problems

Published Online: 04 Jun 2021
Page range: 22 - 30
Journal Details
License
Format
Journal
First Published
08 Nov 2012
Publication timeframe
2 times per year
Languages
English
Abstract

Improving IS (Information System) end-user experience is one of the most important tasks in the analysis of end-users behaviour, evaluation and identification of its improvement potential. However, the application of Machine Learning methods for the UX (User Experience) usability and effic iency improvement is not widely researched. In the context of the usability analysis, the information about behaviour of end-users could be used as an input, while in the output data the focus should be made on non-trivial or difficult attention-grabbing events and scenarios. The goal of this paper is to identify which data potentially can serve as an input for Machine Learning methods (and accordingly graph theory, transformation methods, etc.), to define dependency between these data and desired output, which can help to apply Machine Learning / graph algorithms to user activity records.

Keywords

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