An approach for discovering Multilingual news events and term association from the Web

Hang Chen, Ronghao Wei
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引用次数: 1

Abstract

We have investigated an approach for automatically discovering news events from Web online news downloaded from different sites of different languages. The story content is analyzed. Unsupervised learning is conducted to discover events. From the comparable news stories in the events, statistical analysis of term co-occurrence is developed for mining bilingual term associations. We have conducted some experiments to evaluate our approach on discovering events and term associations. According to the result of the experiment, the approach is a effective way for the discovering Multilingual news events and term association from the web.
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一种从Web上发现多语言新闻事件和术语关联的方法
我们研究了一种从从不同语言的不同网站下载的在线新闻中自动发现新闻事件的方法。对故事内容进行分析。进行无监督学习是为了发现事件。从事件中具有可比性的新闻故事出发,发展了术语共现的统计分析,以挖掘双语术语关联。我们进行了一些实验来评估我们发现事件和术语关联的方法。实验结果表明,该方法是一种从网络中发现多语言新闻事件和术语关联的有效方法。
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