• DocumentCode
    624999
  • Title

    Recognizing High-Level Contexts from Smartphone Built-In Sensors for Mobile Media Content Recommendation

  • Author

    Otebolaku, Abayomi M. ; Andrade, Maria Teresa

  • Author_Institution
    Telecommun. & Multimedia Unit, INESC-TEC Porto, Porto, Portugal
  • Volume
    2
  • fYear
    2013
  • fDate
    3-6 June 2013
  • Firstpage
    142
  • Lastpage
    147
  • Abstract
    Context Recognition is an important element for developing context aware mobile applications. However, context is mostly available as low-level sensor data that are in form not suitable for mobile applications. In this paper, we present a process that uses classifiers for recognizing high-level contexts from low-level sensor data. The process demonstrates accurate recognition of user activity contexts, using smart-phone built-in sensors. We describe and illustrate our context recognition model and then demonstrate its application in a context aware mobile multimedia recommendation system.
  • Keywords
    content management; mobile computing; multimedia systems; recommender systems; sensors; smart phones; context aware mobile applications; context aware mobile multimedia content recommendation system; high-level context recognition; low-level sensor data; mobile applications; smart phone built-in sensors; user activity contexts; Accelerometers; Context; Context modeling; Mobile communication; Multimedia communication; Sensors; Support vector machine classification; classification; context recognition; low-level context data; multimedia; smartphone sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mobile Data Management (MDM), 2013 IEEE 14th International Conference on
  • Conference_Location
    Milan
  • Print_ISBN
    978-1-4673-6068-5
  • Type

    conf

  • DOI
    10.1109/MDM.2013.84
  • Filename
    6569080