2014 | OriginalPaper | Chapter
Improving Mobile Recommendations through Context-Aware User Interaction
Author : Béatrice Lamche
Published in: User Modeling, Adaptation, and Personalization
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Mobile recommender systems provide personalized recommendations to help deal with today’s information overload. However, due to spatial limitations in mobile interfaces and uncertainty of the user’s preferences in the beginning, the improvement of the user experience remains one of the main challenges when designing these systems and has not been investigated thoroughly. This paper describes the aim and progress of the author’s PhD studies on the user interaction, usability and accuracy of mobile recommender systems. The approach aims to combine different user interaction methods with context-awareness to allow user-friendly personalized mobile recommendations.