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Intelligent Natural Language Processing: Trends and Applications pp 373–397Cite as

Using Text Mining Techniques for Extracting Information from Research Articles

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 740))

Abstract

Nowadays, research in text mining has become one of the widespread fields in analyzing natural language documents. The present study demonstrates a comprehensive overview about text mining and its current research status. As indicated in the literature, there is a limitation in addressing Information Extraction from research articles using Data Mining techniques. The synergy between them helps to discover different interesting text patterns in the retrieved articles. In our study, we collected, and textually analyzed through various text mining techniques, three hundred refereed journal articles in the field of mobile learning from six scientific databases, namely: Springer, Wiley, Science Direct, SAGE, IEEE, and Cambridge. The selection of the collected articles was based on the criteria that all these articles should incorporate mobile learning as the main component in the higher educational context. Experimental results indicated that Springer database represents the main source for research articles in the field of mobile education for the medical domain. Moreover, results where the similarity among topics could not be detected were due to either their interrelations or ambiguity in their meaning. Furthermore, findings showed that there was a booming increase in the number of published articles during the years 2015 through 2016. In addition, other implications and future perspectives are presented in the study.

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Author information

Authors and Affiliations

  1. Faculty of Engineering & IT, The British University in Dubai, Dubai, UAE

    Said A. Salloum & Khaled Shaalan

  2. University of Fujairah, Fujairah, UAE

    Said A. Salloum

  3. Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Gambang, Malaysia

    Mostafa Al-Emran

  4. Al Buraimi University College, Buraimi, Oman

    Mostafa Al-Emran

  5. Faculty of Computer & Information Sciences, Ain Shams University, Cairo, Egypt

    Azza Abdel Monem

Authors
  1. Said A. Salloum
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  2. Mostafa Al-Emran
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  3. Azza Abdel Monem
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  4. Khaled Shaalan
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Corresponding author

Correspondence to Said A. Salloum .

Editor information

Editors and Affiliations

  1. The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

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

    Aboul Ella Hassanien

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

    Fahmy Tolba

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Salloum, S.A., Al-Emran, M., Monem, A.A., Shaalan, K. (2018). Using Text Mining Techniques for Extracting Information from Research Articles. In: Shaalan, K., Hassanien, A., Tolba, F. (eds) Intelligent Natural Language Processing: Trends and Applications. Studies in Computational Intelligence, vol 740. Springer, Cham. https://doi.org/10.1007/978-3-319-67056-0_18

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  • DOI: https://doi.org/10.1007/978-3-319-67056-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67055-3

  • Online ISBN: 978-3-319-67056-0

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