new/s/leak – A Tool for Visual Exploration of Large Text Document Collections in the Journalistic Doman
new/s/leak – A Tool for Visual Exploration of Large Text Document Collections in the Journalistic Doman
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new/s/leak – 新闻领域大型文本文档集合的可视化探索工具
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Heiner Ulrich
中科院分区：
文献类型：
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作者：
K. Ballweg;F. Zouhar;Patrick Wilhelmi;T. V. Landesberger;Uli Fahrer;Alexander Panchenko;Seid Muhie Yimam;Chris Biemann;Michaela Regneri;Heiner Ulrich
新闻记者努力为公众报道有新闻价值的新闻。为了找到这些故事，他们需要探索和阅读大量收藏的文件，如基辛格电报。这是非常耗时的，因为文本文档集合太大，无法单独阅读它们-即使是在团队中。交互式文本可视化可以支持记者在这奋进的努力。有几种工具存在，但我们的合作记者的采访揭示了它们的各种缺点。因此，我们开发并提出了一个原型，我们的新系统新的/s/泄漏，它结合了自然语言处理和可视化，专门适应记者的需求。
Journalists strive for newsworthy stories for the public. To find those stories they need to explore and read documents from large collections such as the Kissinger Cables. This is very time consuming, since the the text document collections are too large to read them alone – even in a team. Interactive text visualization can support journalists in this endeavor. Several tools exists, but interviews with our collaboration journalists revealed their various drawbacks. Therefore, we develop and present a prototype of our novel system new/s/leak, which combines natural language processing and visualization adapted specifically to the journalists’ needs.