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Performance Evaluation of SVM-Based Amazighe Named Entity Recognition

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Book cover The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) (AMLTA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 723))

Abstract

A big scope within today’s Amazighe society is the amount of information generated each day, mainly within the print and online press where a lot of articles are written daily and need to be processed in some way to appropriately recognize the content within. Indeed, the Named Entity Recognition (NER) has become one of the most fundamental tasks for several natural language processing applications, where texts are analyzed to locate and classify entities into predefined classes. While many algorithms have been proposed for this task, Amazighe NER remains a challenging task and an active research area. In this paper, we managed to achieve an encouraging performance, close to a state-of-the-art NER performance in other languages. The empirical results show that the proposed system achieves more than 80%, regarding the F-measure, when applied to our testing dataset that we have created manually.

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Notes

  1. 1.

    http://www.hcp.ma/Presentation-des-premiers-resultats-du-RGPH-2014_a1605.html.

  2. 2.

    The articles were collected from: http://www.mapamazighe.ma/am/.

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Author information

Authors and Affiliations

  1. LRIT, Unité Associée Au CNRST, Faculty of Science, Mohammed V University-Agdal, Rabat, Morocco

    Meryem Talha & Driss Aboutajdine

  2. Royal Institut of Amazighe Culture, Allal El Fassi Avenue, Madinat al Irfane, Rabat-Instituts, Rabat, Morocco

    Siham Boulaknadel

Authors
  1. Meryem Talha
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  2. Siham Boulaknadel
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  3. Driss Aboutajdine
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Corresponding author

Correspondence to Meryem Talha .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Computers and Information Sciences, Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

  3. Faculty of Computers and Information, Department of Computer Science and Engineering, Mansoura University, Dakahlia, Egypt

    Mohamed Elhoseny

  4. Arab Academy for Science, Technology and Maritime Transport (AASTMT), Dokki, Egypt

    Mohamed Mostafa

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Talha, M., Boulaknadel, S., Aboutajdine, D. (2018). Performance Evaluation of SVM-Based Amazighe Named Entity Recognition. In: Hassanien, A., Tolba, M., Elhoseny, M., Mostafa, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-74690-6_23

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  • DOI: https://doi.org/10.1007/978-3-319-74690-6_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74689-0

  • Online ISBN: 978-3-319-74690-6

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