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A knowledge-based approach to user interface adaptation from preferences and for special needs

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Abstract

Moving between devices is omnipresent, but not for people with disabilities or those who require specific accessibility options. Setting up assistive technologies or finding settings to overcome a certain barrier can be a demanding task for people without technical skills. Context-sensitive adaptive user interfaces are advancing, although migrating access features from one device to another is very rarely addressed. In this paper, we describe the knowledge-based component of the Global Public Inclusive Infrastructure that infers how a device shall be best configured at the operating system layer, the application layer and the web layer to meet the requirements of a user including possible special needs or disabilities. In this regard, a mechanism to detect and resolve conflicting accessibility policies as well as recommending preference substitutes is a main requirement, as elaborated in this paper. As the proposed system emulates decision-making of accessibility experts, we validated the automatic deduced configurations against manual configurations of ten accessibility experts. The assessment result shows that the average matching score of the developed system is high. Thus, the proposed system can be considered capable of making precise decisions towards personalizing user interfaces based on user needs and preferences.

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Notes

  1. https://terms.raisingthefloor.org/about.

  2. http://www.omnitor.se/products/ecmobile/.

  3. https://github.com/GutiX/chrome4cloud.

  4. https://wiki.gpii.net/w/Preference_Conditions_Format.

  5. https://jena.apache.org/.

  6. https://github.com/claudialoitsch/RuleBasedMatchMaker_RESTful_WS_Maven.

  7. http://www.freedomscientific.com/Products/Blindness/JAWS.

  8. http://www.nvaccess.org/.

  9. https://help.gnome.org/users/orca/3.4/.

  10. https://www.texthelp.com/en-gb.

  11. The object is not represented in Fig. 4. It would be a blue circle that is not connected to any other objects.

  12. http://www.accessible-eu.org/index.php/ontology.html.

  13. http://www.aegis-project.eu/index.php?option=com_content&view=article&id=107&Itemid=65.

  14. https://jena.apache.org/documentation/inference/.

  15. http://webaim.org/projects/screenreadersurvey6/.

  16. An example of the transformation rule of speech rate supported by the screen reader NVDA to the corresponding common term can be found on the GPII repository on GitHub https://github.com/GPII/universal/blob/master/testData/solutions/win32.json5#L917-L965.

  17. http://windows.microsoft.com/en-us/windows/make-screen-items-bigger-magnifier#1TC=windows-7.

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Acknowledgements

We thank all participants that took part in our interviews and user studies. We received meaningful feedback for the design of our approach. Results presented in this paper have been researched within the Cloud4all project. Cloud4all is an R&D project that receives funding from the European Commission under the Seventh Framework Programme (FP7/2007-2013) under Grant Agreement n 289016.

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Authors and Affiliations

  1. Department of Computer Science, Technische Universität Dresden, Mommsenstr. 13, 01602, Dresden, Germany

    Claudia Loitsch & Gerhard Weber

  2. Information Technologies Institute, Centre for Research and Technology Hellas, 6th km Harilaou - Thermi, 57001, Thessaloniki, Greece

    Nikolaos Kaklanis, Konstantinos Votis & Dimitrios Tzovaras

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  1. Claudia Loitsch
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  2. Gerhard Weber
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  3. Nikolaos Kaklanis
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  4. Konstantinos Votis
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  5. Dimitrios Tzovaras
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Correspondence to Claudia Loitsch.

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Loitsch, C., Weber, G., Kaklanis, N. et al. A knowledge-based approach to user interface adaptation from preferences and for special needs. User Model User-Adap Inter 27, 445–491 (2017). https://doi.org/10.1007/s11257-017-9196-z

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