Personalized application recommendations based on application usage and location

Abstract

The purpose of this study is to recommend proper applications to users when they need them based on personal situations and common application usages. We propose application recommendation based on the frequency of an application usage and a location. Application usages and locations are gathered from users' devices and analyzed them at a personal cloud server. Personalized applications can be recommended based on a user's context. In addition, generalized applications can be recommended based on other people' experiences. The application usages should be calculated by the number of application execution by some period. It is important to decide the period. Also, more effective algorithms should be developed. © 2012 Springer Science+Business Media.