Mining history with Le Monde

T. Huet, J. Biega, Fabian M. Suchanek
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引用次数: 37

Abstract

The last decade has seen the rise of large knowledge bases, such as YAGO, DBpedia, Freebase, or NELL. In this paper, we show how this structured knowledge can help understand and mine trends in unstructured data. By combining YAGO with the archive of the French newspaper Le Monde, we can conduct analyses that would not be possible with word frequency statistics alone. We find indications about the increasing role that women play in politics, about the impact that the city of birth can have on a person's career, or about the average age of famous people in different professions.
《世界报》挖掘历史
过去十年见证了大型知识库的兴起,如YAGO、DBpedia、Freebase或NELL。在本文中,我们展示了这种结构化知识如何帮助理解和挖掘非结构化数据中的趋势。通过将YAGO与法国报纸《世界报》(Le Monde)的档案相结合,我们可以进行单独使用词频统计无法进行的分析。我们发现了一些迹象,比如女性在政治中发挥的作用越来越大,出生城市对一个人的职业生涯的影响越来越大,或者不同行业名人的平均年龄也有所不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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