DocumentCode :
1646755
Title :
Personalized and adaptive user interface framework for mobile application
Author :
Nivethika, Mahasivam ; Vithiya, Ilanthalaisingam ; Anntharshika, Sebastiankularatnam ; Deegalla, Sampath
Author_Institution :
Dept. of Comput. Eng., Univ. of Peradeniya, Peradeniya, Sri Lanka
fYear :
2013
Firstpage :
1913
Lastpage :
1918
Abstract :
User interfaces in mobile applications are complex since they need to provide sufficient features to variety of users in a restricted space where a small number of components are available. When user acquires expertise in the system they expect user interfaces which satisfy their unique needs. Therefore, user interfaces in mobile applications should be adapted to different users. Since this problem exists in various applications a general solution is required to make user interfaces adaptive using user context history. In this paper, we introduce a conceptual prototype framework for mobile applications to make the user interfaces adaptive to the user. This identifies a suitable experience level to a user by learning his/her history of interactions with applications and then displays adaptive user interfaces. A proof of concept application is implemented to inspect the behavior of framework. Further, a user study was conducted on the developed proof of concept application and user context data was stored. This data was used as the training data for the Inference engine. This framework introduces an abstract solution which can be used to adapt various user interfaces based on human computer interactions. We believe the suggested framework can be used in related adaptation for Web applications, desktop applications and other mobile platforms.
Keywords :
graphical user interfaces; human computer interaction; inference mechanisms; interactive systems; learning (artificial intelligence); mobile computing; Web applications; abstract solution; conceptual prototype framework; desktop applications; human computer interactions; inference engine; mobile application; personalized adaptive user interface framework; training data; user context history; user experience level; user interaction history; Androids; Context; Engines; Humanoid robots; Mobile communication; Rendering (computer graphics); User interfaces; AI and expert systems; HCI in Mobile; adaptive user interface framework; k-means algorithm; machine learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4799-2432-5
Type :
conf
DOI :
10.1109/ICACCI.2013.6637474
Filename :
6637474
Link To Document :
بازگشت