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An Automatic Online News Topic Keyphrase Extraction System

机译:自动在线新闻主题关键级提取系统

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摘要

News Topics are related to a set of keywords or keyphrases. Topic keyphrases briefly describe the key content of topics and help users decide whether to do further reading about them. Moreover, keyphrases of a news topic can be considered as a cluster of related terms, which provides term relationship information that can be integrated into information retrieval models. In this paper, an automatic online news topic keyphrase extraction system is proposed. News stories are organized into topics. Keyword candidates are firstly extracted from single news stories and filtered with topic information. Then a phrase identification process combines keywords into phrases using position information. Finally, the phrases are ranked and top ones are selected as topic keyphrases. Experiments performed on practical Web datasets show that the proposed system works effectively, with a performance of precision=70.61% and recall=67.94%.
机译:新闻主题与一组关键字或密钥段相关。主题Keyphrass简要描述主题的关键内容,并帮助用户决定是否进一步阅读它们。此外,新闻主题的关键短址可以被视为相关术语群集,其提供可以集成到信息检索模型中的术语关系信息。在本文中,提出了一种自动在线新闻主题关键正版提取系统。新闻故事被组织成主题。首先从单一新闻故事中提取关键字候选,并通过主题信息过滤。然后,使用位置信息,短语识别过程将关键字组合成短语。最后,将短语排列,并选择顶部作为主题kephrase。在实际网络数据集上进行的实验表明,该系统有效地工作,具有精度= 70.61%,召回= 67.94%。

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