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
Link To Document :
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