Personalized Recommender System for Smartphones based on Application Usage
The rebellious growth of the mobile application market has made it a significant challenge for the users to find relevant applications in crowded application stores. To diminish this problem, existing solutions often use the user’s application-download history or user-rating to recommend applications that might interest them. However, the user downloading an application does not indicate that the user likes that application. Using user-ratings, on the other hand, suffers from tedious manual input and potential data insufficiency problems.