基于网格聚类的数据流多事件检测  

Multiple Event Detection Over Data Streams Using Grid-Based Clustering

作　　者：袁志坚[1] 缪嘉嘉[1] 杜凯[1] 贾焰[1] 

机构地区：[1]国防科技大学计算机学院,湖南长沙410073

出　　处：《计算机工程与科学》2008年第9期82-85,共4页Computer Engineering & Science

基　　金：国家863计划资助项目(2006AA01Z451);国防预研基金资助项目

摘　　要：事件检测是事件处理系统最重要的研究问题之一。异常、变化和突发是三类最典型的数据流事件。本文关注如何在数据流中同时检测多种事件,首先研究了多种事件之间的联系,然后给出了基于网格聚类的统一处理方法,最后为了评估事件的严重程度,给出了打分函数。实验验证了所提方法的正确性与有效性。Event detection is one of the most important issues in event processing systems. Outlier, change and burst are three typical types of events. We address how to detect multiple types of events simultaneously. In this paper,we first explore the relationship of these three types of events, and then present a unified method for dealing with all of them by using grid-based clustering. In order to evaluate the events, several score functions are defined for each type of events as well. Simulation results testify the efficiency of the proposed framework.

关 键 词：数据流 数据挖掘 事件检测 网格聚类 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]