• DocumentCode
    3728360
  • Title

    Analysis of Actual Smartphone Logs for Predicting the User´s Routine Settings of Application Volume

  • Author

    Tatsuhito Hasegawa;Makoto Koshino;Haruhiko Kimura

  • Author_Institution
    Div. of Healthcare Inf., Tokyo Healthcare Univ., Tokyo, Japan
  • fYear
    2015
  • Firstpage
    2654
  • Lastpage
    2659
  • Abstract
    Although the volume settings of smartphones are important for users, they still need to push the hardware sound button manually. The purpose of our study is to improve the usability of volume settings. Our proposed method predicts the user´s routine volume settings by learning the actual daily smartphone logs. Related works used suitable volume settings input by the experimental participants to learn the volume setting pattern for each user. In contrast, this study uses actual smartphone logs. This paper describes three results of the analyses of many actual smartphone logs. First, we investigate the rate at which the users change the application volume. Second, we examine the accuracy of the results predicted by our method. Third, we classify the test users as users for whom our method effectively works or others. Finally, we discuss the appropriateness of the predicted results for users´ routine settings.
  • Keywords
    "Turning","Motion pictures","Machine learning algorithms","Batteries","Games","Smart phones","Switches"
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/SMC.2015.464
  • Filename
    7379596