<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

Applied Computer Systems

This work is licensed under the Creative Commons Attribution 4.0 International License.

Improving IS (Information System) end-user experience is one of the most important tasks in the analysis of end-users behaviour, evaluation and identification...

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

Online veröffentlicht: 04. Juni 2021

Seitenbereich: 22 - 30

DOI: https://doi.org/10.2478/acss-2021-0003

Schlüsselwörter
Data mapping, IS usability, Machine Learning, User Experience (UX)

© 2021 Oksana Ņikiforova et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Online veröffentlicht: 04. Juni 2021

Seitenbereich: 22 - 30

DOI: https://doi.org/10.2478/acss-2021-0003

SchlüsselwörterData mapping, IS usability, Machine Learning, User Experience (UX)

© 2021 Oksana Ņikiforova et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Data mapping, IS usability, Machine Learning, User Experience (UX)