A Context-Aware Usage Prediction Approach for Smartphone Applications

  • Jingjing Huangfu
  • Jian CaoEmail author
  • Chenyang Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9464)


With the popularity of smartphones, an increasing number of applications (app) are installed on common users’ smartphones. As a result, it is becoming difficult to find the right apps to use promptly. Based on the observation from the real data, it can be found the correlative relationship exists between the usage of app and the context, specifically, time and location contextual information. According to this analysis, a context-aware usage prediction model is proposed to predict the probability of launching apps and present this prediction by an ordered list. Furthermore, a dynamic desktop application for android platform is developed to adjust the app icon order on the desktop according to the current time and location information, which facilitates the smartphone users always capable finding their needed ones in the first page. The experiments show that our prediction model outperforms other approaches.


Context-aware Mobile app Usage prediction model Dynamic android desktop 



This work is partially supported by China National Science Foundation (Granted Number 61272438,61472253), Research Funds of Science and Technology Commission of Shanghai Municipality (Granted Number 15411952502, 12511502704).


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina

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