Journal article

Smartphone App Usage Prediction Using Points of Interest

D Yu, Y Li, F Xu, P Zhang, V Kostakos

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies | Association for Computing Machinery | Published : 2018


In this paper we present the first population-level, city-scale analysis of application usage on smartphones. Using deep packet inspection at the network operator level, we obtained a geo-tagged dataset with more than 6 million unique devices that launched more than 10,000 unique applications across the city of Shanghai over one week. We develop a technique that leverages transfer learning to predict which applications are most popular and estimate the whole usage distribution based on the Point of Interest (POI) information of that particular location. We demonstrate that our technique has an 83.0% hitrate in successfully identifying the top five popular applications, and a 0.15 RMSE when e..

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