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AI – Based Approach for Mobile User Interface Adaptation

Authors:
Hajer Dammak
Meriem Riahi
Faouzi Moussa

Keywords: Adaptation; Mobile User Interface; User Behavior; Log File; Artificial Intelligence; Machine Learning.

Abstract:
The technological evolution and the advent of smart mobile devices have profoundly changed the daily lives of users. Indeed, users are particularly focused on their smartphones in order to manage their activities, check their emails, follow the news, connect to social networks, etc. Despite the impressive technological evolution of smartphones, the user interface remains below expectations of users, especially in terms of adaptation. Parallel to the technological evolution, Artificial Intelligence (AI) has also progressed very significantly. This discipline can improve user-smartphone interaction. Indeed, Machine Learning (ML), for example, offers effective means to adapt the interface according to the habits and changes in the behavior of the user. The goal here is to dynamically reorganize the mobile interfaces by grouping the frequently used applications so they will be more efficiently accessible by users. In this sense, the smartphone’s log files are used to make better data-driven decisions. These logs will be exploited in a ML approach to model the user's behavior and to propose adaptations. In this paper, we discuss the user feedback for the first results of grouping icons.

Pages: 310 to 316

Copyright: Copyright (c) IARIA, 2020

Publication date: March 22, 2020

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-61208-761-0

Location: Valencia, Spain

Dates: from November 21, 2020 to November 25, 2020