Live blogs are an increasingly popular news format to cover breaking news and live events in online journalism. Online news websites around the world are using this medium to give their readers a minute by minute update on an event. Good summaries enhance the value of the live blogs for a reader, but are often not available. In this article, (a) we first define the task of summarizing a live blog, (b) study ways of automatically collecting corpora for live blog summarization, and (c) understand the complexity of the task by empirically evaluating well-known state-of-the-art unsupervised and supervised summarization systems on our new corpus. We show that live blog summarization poses new challenges in the field of news summarization, since frequency and positional signals cannot be used. We make our tools publicly available to reconstruct the corpus and to conduct our empirical experiments. This encourages the research community to build upon and replicate our results.

实时博客是一种越来越流行的新闻格式，涵盖在线新闻中的重大新闻和实时事件。世界各地的在线新闻网站都使用这种媒体向读者提供有关事件的最新消息。好的摘要可以提高实时博客对读者的价值，但通常不可用。在本文中，（a）我们首先定义了实时博客摘要的任务，（b）研究了自动收集语料库以进行实时博客摘要的方法，并且（c）通过实证评估众所周知的状态来了解任务的复杂性-新语料库上最先进的无监督和监督摘要系统。我们表明，实时博客摘要在新闻摘要领域提出了新的挑战，因为无法使用频率和位置信号。我们公开提供了用于重建语料库和进行经验实验的工具。这鼓励研究界在我们的研究结果的基础上进行复制。