• DocumentCode
    2652676
  • Title

    A Real-Time Burst Detection Method

  • Author

    Ebina, Ryohei ; Nakamura, Kenji ; Oyanagi, Shigeru

  • Author_Institution
    Ritsumeikan Univ., Kusatsu, Japan
  • fYear
    2011
  • fDate
    7-9 Nov. 2011
  • Firstpage
    1040
  • Lastpage
    1046
  • Abstract
    Real-time burst detection over multiple window size is useful for analyzing data streams. Various burst detection methods have been proposed. However, they are not effective for real-time detection. This work proposes a new burst detection method that reduces computation by avoiding redundant data updates. It analyses an event on its occurrence, and detects the period where arrival frequency rises rapidly to the previous period. In addition, it reduces computation by suppressing data within a certain period even in the case of emergent increase of events. The effectiveness of the proposed method is evaluated by experiments with real data.
  • Keywords
    data analysis; real-time systems; arrival frequency; computation reduction; data stream analysis; multiple window size; real-time burst detection method; redundant data update avoidance; Aggregates; Blogs; Data structures; Detection algorithms; Real time systems; Time frequency analysis; Time series analysis; algorithm; burst detection; data mining; data stream; real-time;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
  • Conference_Location
    Boca Raton, FL
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4577-2068-0
  • Electronic_ISBN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2011.177
  • Filename
    6103468