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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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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