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

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10859)


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.


Event extraction Arabic language Terms weighting Morphological analysis 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.RIADI Research LaboratoryENSI, Manouba UniversityManoubaTunisia
  2. 2.National Engineering School of SousseSousse UniversitySousseTunisia
  3. 3.Emirates College of TechnologyAbu DhabiUnited Arab Emirates

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