标题： 目标事件检测 显示英文标题

标题： Targeted Event Detection

摘要： 我们考虑基于描述某个系统的（通常是多变量的）数据流进行事件检测的问题。 大多数时候系统是静止的——没有值得关注的事情发生——但偶尔会有一些值得关注的事件发生。 事件检测的目标是在事件开始后尽快发出警报。 解决事件检测问题的一种简单方法是寻找数据流中的变化，并将“变化”等同于“事件的开始”。 然而，流中可能会有许多不值得关注的变化。 我们假设我们得到一个流的片段，其中已经标记了值得关注的事件。 我们提出一种方法，利用这些训练数据构建一个“针对性”的检测器，该检测器专门对表明值得关注的事件开始的变化敏感。 显示英文摘要

摘要： We consider the problem of event detection based upon a (typically multivariate) data stream characterizing some system. Most of the time the system is quiescent - nothing of interest is happening - but occasionally events of interest occur. The goal of event detection is to raise an alarm as soon as possible after the onset of an event. A simple way of addressing the event detection problem is to look for changes in the data stream and equate `change' with `onset of event'. However, there might be many kinds of changes in the stream that are uninteresting. We assume that we are given a segment of the stream where interesting events have been marked. We propose a method for using these training data to construct a `targeted' detector that is specifically sensitive to changes signaling the onset of interesting events.