A Mobile Application Recommendation Framework by Exploiting Personal Preference with Constraints

Abstract EN

Explosive mobile applications (Apps) are proliferating with the popularity of mobile devices (e.g., smartphones, tablets).

These Apps are developed to satisfy different function needs of users.

Majority of existing App Stores have difficulty in recommending proper Apps for users.

Therefore, it is of significance to recommend mobile Apps for users according to personal preference and various constraints of mobile devices (e.g., battery power).

In this paper, we propose a mobile App recommendation framework by incorporating different requirements from users.

We exploit modern portfolio theory (MPT) to combine the popularity of mobile Apps, personal preference, and mobile device constraints for mobile App recommendation.

Based on this framework, we discuss the recommendation approaches by constraints of phone power and limited mobile data plan.

Extensive evaluations show that the proposed mobile App recommendation framework can well adapt to power and network data plan constraints.

It satisfies the user App preference and mobile device constraints.