从推特流中实时总结预定事件

A. Zubiaga, Damiano Spina, Enrique Amigó, Julio Gonzalo
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引用次数: 108

摘要

我们通过以下两个步骤来处理实时缩减计划事件的推文流:(i)子事件检测,确定是否发生了新的事情;(ii)推文选择,选择一条推文来描述每个子事件。通过将三种语言的摘要与记者的现场报道进行比较,我们发现,不涉及外部知识的简单文本分析方法可以平均覆盖84%的子事件,以及100%的关键类型的子事件(如足球进球)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards real-time summarization of scheduled events from twitter streams
We deal with shrinking the stream of tweets for scheduled events in real-time, following two steps: (i) sub-event detection, which determines if something new has occurred, and (ii) tweet selection, which picks a tweet to describe each sub-event. By comparing summaries in three languages to live reports by journalists, we show that simple text analysis methods which do not involve external knowledge lead to summaries that cover 84% of the sub-events on average, and 100% of key types of sub-events (such as goals in soccer).
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