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Interactive, Domain-Independent Identification and Summarization of Topically Related News Articles

机译:互动,域名独立的识别和题目相关新闻文章的总结

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In this paper we present NewsInEssence, a fully deployed digital news system. A user selects a current news story of interest which is used as a seed article by NewsInEssence to find in real time other related stories from a large number of news sources. The output is a single document summary presenting the most salient information gleaned from the different sources. We discuss the algorithm used by NewsInEssence, module interoperability, and conclude the paper with a number of empirical analyses.
机译:在本文中,我们提供了一个完全部署的数字新闻系统的新闻。用户选择当前的兴趣新闻故事,这些故事用作种子文章通过新闻中的实时查找,从大量的新闻来源中找到其他相关故事。输出是单个文档摘要,呈现来自不同来源的最突出的信息。我们讨论了新闻,模块互操作性,并以许多经验分析结束了纸张。

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