Millions of news articles from hundreds of thousands of sources around the globe appear in news aggregators every day. Consuming such a volume of news presents an almost insurmountable challenge. For example, a reader searching on Bloomberg's system for news about the U.K. would find 10,000 articles on a typical day. Apple Inc., the world's most journalistically covered company, garners around 1,800 news articles a day. We realized that a new kind of summarization engine was needed, one that would condense large volumes of news into short, easy to absorb points. The system would filter out noise and duplicates to identify and summarize key news about companies, countries or markets. When given a user query, Bloomberg's solution, Key News Themes (or NSTM), leverages state-of-the-art semantic clustering techniques and novel summarization methods to produce comprehensive, yet concise, digests to dramatically simplify the news consumption process. NSTM is available to hundreds of thousands of readers around the world and serves thousands of requests daily with sub-second latency. At ACL 2020, we will present a demo of NSTM.
翻译：来自全球数十万来源的数以百万计的新闻文章每天出现在新闻汇总器中。 如此一大批新闻呈现出几乎不可克服的挑战。 例如, 读者在Bloomberg的系统搜索关于英国的新闻时, 会在典型的一天找到一万篇文章。 世界上报道最多的公司苹果公司( Apple Inc. Inc.) 每天收集约1 800篇新闻文章。 我们认识到, 需要一种新型的汇总引擎, 将大量新闻压缩为简短的、容易吸收的点。 该系统将过滤噪音和复制品, 以识别和总结有关公司、 国家或市场的关键新闻。 当用户查询时, 将使用Bloomberg 的解决方案、 关键新闻主题( NSTM ), 利用最先进的语义组合技术和新颖的汇总方法来制作全面但简洁的简洁摘要, 以大幅简化新闻消费过程。 国家通信管理系统可以向世界各地成千上万的读者提供, 并每天为数千个请求提供次拉特。 在 ACL 2020 时, 我们将提供一份 NSTM TM 的图像 。
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