Nihao: A Predictive Smartphone Application Launcher

  • Chunhui Zhang
  • Xiang Ding
  • Guanling Chen
  • Ke Huang
  • Xiaoxiao Ma
  • Bo Yan
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 110)

Abstract

Increasingly large number of the applications installed on smartphones tends to harm the application lookup efficiency. In this paper, we introduce Nihao, a personalized intelligent app launcher system, which could help the users to find apps quickly. Nihao predicts which app the user will likely open next based on a Bayesian Network model leveraging the contextual information such as the time of day, the day of week, the user’s location and the last used app with the hypothesis that the users’ app usage pattern is context dependent. Through the field study with seven users over six weeks, we first validate the above hypothesis by comparing the prediction accuracy of Nihao with other predictors. We found that the larger UI change did not necessarily yield longer app lookup time as the app lookup time highly depended on the app icon position on screen, which suggested the prediction accuracy was the most important factor in designing such a system. At the end of the study, we conducted a user survey to evaluate Nihao qualitatively. The survey results show that five out of seven users were quite satisfied with the prediction of Nihao and thought it could help to save both app lookup and management time by ranking the app icons automatically while Nihao did not help the other two users much since they used their phones primarily for calling and texting (not for apps).

Keywords

mobile applications Android applications application usage prediction context awareness adaptive UI 

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Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2013

Authors and Affiliations

  • Chunhui Zhang
    • 1
  • Xiang Ding
    • 1
  • Guanling Chen
    • 1
  • Ke Huang
    • 1
  • Xiaoxiao Ma
    • 1
  • Bo Yan
    • 1
  1. 1.Computer Science DepartmentUniversity of Massachusetts LowellLowellUSA

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