Main Reference PaperMobile big-data-driven rating framework: measuring the relationship between human mobility and app usage behavior, IEEE Transactions on Network, 2016 [Java].
  • In focus on impact of both crowd and individual mobility behavior on app usage. To predict the app usage behavior from the temporal and spatial dimensions in a statistical manner and rating framework is proposed. A rating framework is designed to process traffic traces, select the significant features of human mobility, and forecast the app usage behavior.

+ Description
  • In focus on impact of both crowd and individual mobility behavior on app usage. To predict the app usage behavior from the temporal and spatial dimensions in a statistical manner and rating framework is proposed. A rating framework is designed to process traffic traces, select the significant features of human mobility, and forecast the app usage behavior.

  • To predict the app usage behavior of crowds and individuals.

  • To achieve the high forecast accuracy.

+ Aim & Objectives
  • To predict the app usage behavior of crowds and individuals.

  • To achieve the high forecast accuracy.

  • This work contributes more applications will be studied through using the larger dataset. Specifically, a new model is expected to be proposed to predict individual app usage behavior based on our rating framework.

+ Contribution
  • This work contributes more applications will be studied through using the larger dataset. Specifically, a new model is expected to be proposed to predict individual app usage behavior based on our rating framework.

  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1 and J2SE.

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1 and J2SE.

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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