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Related Terms Extraction from Arabic News Corpus Using Word Embedding

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On the Move to Meaningful Internet Systems: OTM 2018 Workshops (OTM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11231))

Abstract

Different techniques are used in text mining to analyze data, extract knowledge, information and relations. We aim in this work to extract related terms for specific keywords. In the first step, we extract Arabic keywords from news articles titles using the TF-IDF terms weighting measure. In the next step, we extract the related terms, from both titles and main texts, using Word2Vec model as a word embedding technique. In order to evaluate our proposed approach, we compute the precision values of the extracted terms that are present in Wikipedia articles. The experiments results perform better for the extracted terms from the articles main texts than titles and the international news category has the highest precision value.

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Notes

  1. 1.

    http://www.arabicnlp.pro/.

  2. 2.

    https://deeplearning4j.org.

  3. 3.

    https://antcorpus.github.io/.

  4. 4.

    https://ar.wikipedia.org.

References

  1. Gök, A., Waterworth, A., Shapira, P.: Use of web mining in studying innovation. Scientometrics 102(1), 653–671 (2015)

    Article  Google Scholar 

  2. Salloum, S.A., AlHamad, A.Q., Al-Emran, M., Shaalan, K.: A survey of Arabic text mining. Intell. Nat. Lang. Process. Trends Appl. Stud. Comput. Intell. 740, 417–431 (2018)

    Google Scholar 

  3. Elayeb, B.: Arabic word sense disambiguation: a review. Artif. Intell. Rev. 50, 1–58 (2018)

    Article  Google Scholar 

  4. Elayeb, B., Bounhas, I.: Arabic cross-language information retrieval: a review. ACM Trans. Asian Low-Resour. Lang. Inf. Process. 15(3), 18:1–18:44 (2016)

    Article  Google Scholar 

  5. Bounhas, I., Elayeb, B., Evrard, F., Slimani, Y.: Organizing contextual knowledge for Arabic text disambiguation and terminology extraction. Knowl. Organ. 38(6), 473–490 (2011)

    Google Scholar 

  6. Al-Mahmoud, H., Al-Razgan, M.: Arabic text mining: a systematic review of the published literature 2002–2014. In: Proceedings of ICCC, pp. 1–7 (2015)

    Google Scholar 

  7. Alhawarat, M., Hegazi, M., Hilal, A.: Processing the text of the Holy Quran: a text mining study. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 6(2), 262–267 (2015)

    Google Scholar 

  8. Harrag, F.: Text mining approach for knowledge extraction in Sahîh Al-Bukhari. Comput. Hum. Behav. 30, 558–566 (2013)

    Article  Google Scholar 

  9. Al-Horaibi, L., Khan, M.B.: Sentiment analysis of Arabic tweets using text mining techniques. In: First International Workshop on Pattern Recognition (2016)

    Google Scholar 

  10. Chan, H.K., Lacka, E., Yee, R.W., Lim, M.K.: A case study on mining social media data. In: Proceedings of 2014 IEEE International Conference on Industrial Engineering and Engineering Management, pp. 593–596 (2014)

    Google Scholar 

  11. Cherif, W., Madani, A., Kissi, M.: A new modeling approach for Arabic opinion mining recognition. In: Proceedings of Intelligent Systems and Computer Vision (ISCV), pp. 1–6 (2015)

    Google Scholar 

  12. Rushdi-Saleh, M., Martín-Valdivia, M.T., Ureña-López, L.A., Perea-Ortega, J.M.: OCA: opinion corpus for Arabic. J. Am. Soc. Inf. Sci. 62(10), 2045–2054 (2011)

    Article  Google Scholar 

  13. Atlam, E.S., Morita, K., Fuketa, M., Aoe, J.I.: A new approach for Arabic text classification using Arabic field-association terms. J. Am. Soc. Inf. Sci. 62(11), 2266–2276 (2011)

    Article  Google Scholar 

  14. Wahsheh, H.A., Alsmadi, I.M., Al-Kabi, M.N.: Analyzing the popular words to evaluate spam in Arabic web pages. Res. Bull. Jordan ACM 11(11), 22–26 (2012)

    Google Scholar 

  15. Larkey, L.S., Ballesteros, L., Connell, M.E.: Light stemming for Arabic information retrieval. In: Soudi, A., Bosch, A., Neumann, G. (eds.) Arabic Computational Morphology. Text, Speech and Language Technology, vol. 38, pp. 221–243 (2007). Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6046-5_12

  16. Chowdhury, A., Aljlayl, M., Jensen, E.C., Beitzel, S.M., Grossmanand, D.A., Frieder, O.: IIT at TREC 2002 linear combinations based on document structure and varied stemming for Arabic retrieval. In: Proceedings of TREC 2002, pp. 299–310 (2002)

    Google Scholar 

  17. Mikolov, T., Sutskever, I., Chen, K., Corrado, G., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Proceedings of NIPS 2013, pp. 3111–3119 (2013)

    Google Scholar 

  18. Chouigui, A., Ben Khiroun, O., Elayeb, B.: ANT corpus: an Arabic news text collection for textual classification. In: Proceedings of AICCSA 2017, pp. 135–142 (2017)

    Google Scholar 

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Author information

Authors and Affiliations

  1. RIADI Research Laboratory, ENSI, Manouba University, 2010, Manouba, Tunisia

    Amina Chouigui, Oussama Ben Khiroun & Bilel Elayeb

  2. National Engineering School of Sousse, ENISO, Sousse University, 4002, Sousse, Tunisia

    Amina Chouigui & Oussama Ben Khiroun

  3. Emirates College of Technology, P.O. Box: 41009, Abu Dhabi, United Arab Emirates

    Bilel Elayeb

Authors
  1. Amina Chouigui
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  2. Oussama Ben Khiroun
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  3. Bilel Elayeb
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Corresponding author

Correspondence to Amina Chouigui .

Editor information

Editors and Affiliations

  1. Trinity College Dublin, Dublin, Ireland

    Christophe Debruyne

  2. University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  3. Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg

    Wided Guédria

  4. Maastricht University, Maastricht, The Netherlands

    Peter Bollen

  5. University Babes-Bolyai, Cluj-Napoca, Romania

    Ioana Ciuciu

  6. TU Graz, Graz, Austria

    Robert Meersman

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Chouigui, A., Ben Khiroun, O., Elayeb, B. (2019). Related Terms Extraction from Arabic News Corpus Using Word Embedding. In: Debruyne, C., Panetto, H., Guédria, W., Bollen, P., Ciuciu, I., Meersman, R. (eds) On the Move to Meaningful Internet Systems: OTM 2018 Workshops. OTM 2018. Lecture Notes in Computer Science(), vol 11231. Springer, Cham. https://doi.org/10.1007/978-3-030-11683-5_26

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  • DOI: https://doi.org/10.1007/978-3-030-11683-5_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11682-8

  • Online ISBN: 978-3-030-11683-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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