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

  • Amina Chouigui
  • Oussama Ben Khiroun
  • Bilel Elayeb
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10859)

Abstract

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.

Keywords

Event extraction Arabic language Terms weighting Morphological analysis 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Amina Chouigui
    • 1
    • 2
  • Oussama Ben Khiroun
    • 1
    • 2
  • Bilel Elayeb
    • 1
    • 3
  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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