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Machine Learning Approach for the Automatic Annotation of Events

机译:机器学习方法,用于自动注释事件

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After the beginning of the extension of current Web towards the semantics, the annotation starts to take a significant role, since it takes part to give the semantic aspect to the different types of documents. With the proliferation of news articles from thousands of different sources now available on the Web, summarization of such information is becoming increasingly important. We will define a methodological approach to extract the events from the news articles and to annotate them according to the principal events which they contain. Considering the large number of news source (for examples, BBC, Reuters, CNN...), every day, thousands of articles are produced in the entire world concerning a given event. This is why we have to think to automate the process of annotation of such articles.
机译:在当前Web扩展到语义的开始后,注释开始取得重要作用,因为它需要将语义方面提供给不同类型的文档。随着网上上市的数千个不同来源的新闻文章的扩散,这些信息的总结变得越来越重要。我们将定义一种方法方法,可以从新闻文章中提取事件,并根据它们包含的主要事件向其注释。考虑到大量的新闻来源(例如,例如,BBC,路透社,CNN ......),每天都在整个世界中制作了有关给定事件的全球成千上万的文章。这就是为什么我们必须认为自动化这些文章的注释过程。

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