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Intelligent Natural Language Processing: Trends and Applications pp 761–776Cite as

A Tutorial on Information Retrieval Using Query Expansion

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

Abstract

Most successful information retrieval techniques which has the ability to expand the original query with additional terms that best represent the actual user need. This tutorial gives an overview of information retrieval models which are based on query expansion along with practical details and description on methods of implementation. Toy examples with data are provided to assist the reader to grasp the main idea behind the query expansion (QE) techniques such as Kullback-Leibler Divergence (KLD) and the candidate expansion terms based on WordNet. The tutorial uses spectral analysis which one of the recent information retrieval techniques that considers the term proximity.

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Author information

Authors and Affiliations

  1. Faculty of Computing and Information Technology, Department of Computing Science, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Mohamed Yehia Dahab, Sara Alnofaie & Mahmoud Kamel

Authors
  1. Mohamed Yehia Dahab
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  2. Sara Alnofaie
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  3. Mahmoud Kamel
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Corresponding author

Correspondence to Mohamed Yehia Dahab .

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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Dahab, M.Y., Alnofaie, S., Kamel, M. (2018). A Tutorial on Information Retrieval Using Query Expansion. 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_35

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  • DOI: https://doi.org/10.1007/978-3-319-67056-0_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67055-3

  • Online ISBN: 978-3-319-67056-0

  • eBook Packages: EngineeringEngineering (R0)

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