从文本源中检测新的和正在出现的事件

Kirk Roberts, S. Harabagiu
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引用次数: 0

摘要

识别新闻文档流中的新事件和新兴事件需要理解用自然语言报道的新闻的语义结构。新事件检测(NED)是一项识别新闻文档何时讨论了一个全新事件的任务。为了成功完成这项任务,我们认为NED方法必须提取和表示事件及其参与者的类型以及事件的时间和空间属性。我们的NED方法比词汇袋基线成本降低了25%,比现有的最先进方法成本降低了13%。此外,我们还讨论了识别新事件的方法:对意外事件或新事件的跟踪和分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting New and Emerging Events from Textual Sources
Recognizing new and emerging events in a stream of news documents requires understanding the semantic structure of news reported in natural language. New event detection (NED) is the task of recognizing when a news document discusses a completely novel event. To be successful at this task, we argue a NED method must extract and represent the type of event and its participants as well as the temporal and spatial properties of the event. Our NED methods produce a 25% cost reduction over a bag-of-words baseline and a 13% cost reduction over an existing state-of-the-art approach. Additionally, we discuss our method for recognizing emerging events: the tracking and categorization of unexpected or novel events.
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