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A TF-IDF and Co-occurrence Based Approach for Events Extraction from Arabic News Corpus

机译:一种基于TF-IDF和共现的阿拉伯新闻语料库事件提取方法

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摘要

Event extraction is a common task for different applications such as text summarization and information retrieval. We propose, in this work, a TF-IDF based approach for extracting keywords from Arabic news articles' titles. These keywords will serve to extract the main events for each month using a Part-of-Speech (POS) co-occurrence based approach. The precision values are computed by corresponding the extracted events with another news website. Results show that the approach performance depends on categories and performs well for domain specific ones such as economy.
机译:事件提取是文本摘要和信息检索等不同应用程序的常见任务。在这项工作中,我们建议使用一种基于TF-IDF的方法从阿拉伯新闻文章标题中提取关键字。这些关键字将使用基于词性(POS)共现的方法来提取每个月的主要事件。通过将提取的事件与另一个新闻网站对应来计算精度值。结果表明,该方法的性能取决于类别,并且对于特定领域的方法(例如经济)表现良好。

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