Learning Geographical and Mobility Factors for Mobile Application Recommendation

With myriad features and functionalities, mobile app users have the option to run different types of apps when they move to different locations. For a specific place, the decision process involved in choosing a mobile app can be complex and influenced by various factors, such as app popularity, user preferences, geographical influences, and user mobility behaviors. Although several researchers have studied recommendation in mobile apps, they omitted an integrated analysis of the joint effect of multiple factors from a geographical perspective. This article proposes a novel location-based probabilistic factor analysis mechanism that considers multiple factors to help people visiting a new location get an appropriate mobile app recommendation. In particular, the authors model mobile app usage from a geographical perspective. Experimental results on real mobile usage data show that the proposed recommendation method outperforms baseline algorithms by 30 percent.