• DocumentCode
    1982425
  • Title

    Mobile Data Stream Mining: From Algorithms to Applications

  • Author

    Krishnaswamy, Shonali ; Gama, Joao ; Gaber, Mohamed Medhat

  • Author_Institution
    Inst. for Infocomm Res. (I2R), Monash Univ., Clayton, VIC, Australia
  • fYear
    2012
  • fDate
    23-26 July 2012
  • Firstpage
    360
  • Lastpage
    363
  • Abstract
    This paper presents an overview of the current state-of-the-art in mobile data stream mining. This area of mobile data stream mining is significant for a number of new application domains such as mobile crowd sensing and mobile activity recognition. The paper presents the strategies and techniques for adaptation that are essential in order to perform real-time, continuous data mining on mobile devices. We present an overview of the algorithms research in this area. Finally, we discuss the key toolkits, systems and applications of mobile data stream mining.
  • Keywords
    data mining; mobile computing; mobile handsets; continuous data mining; mobile activity recognition; mobile crowd sensing; mobile data stream mining; mobile devices; Accuracy; Algorithm design and analysis; Data mining; Data visualization; Distributed databases; Mobile communication; Mobile handsets; Data Stream Mining; Mobile Data Mining; Ubiquitous Data Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mobile Data Management (MDM), 2012 IEEE 13th International Conference on
  • Conference_Location
    Bengaluru, Karnataka
  • Print_ISBN
    978-1-4673-1796-2
  • Electronic_ISBN
    978-0-7695-4713-8
  • Type

    conf

  • DOI
    10.1109/MDM.2012.37
  • Filename
    6341420