一种实时突发检测方法

Ryohei Ebina, Kenji Nakamura, S. Oyanagi
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引用次数: 23

摘要

多窗口大小的实时突发检测对于分析数据流非常有用。人们提出了各种突发检测方法。然而,它们对实时检测并不有效。本文提出了一种新的突发检测方法,通过避免冗余数据更新来减少计算量。它对事件的发生进行分析,并检测到达频率比前一个周期迅速上升的时间段。此外,即使在突发事件增加的情况下,它也可以在一定时间内抑制数据,从而减少计算量。通过实际数据的实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Real-Time Burst Detection Method
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.
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