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International Conference on Database and Expert Systems Applications

DEXA 2016: Database and Expert Systems Applications pp 410–417Cite as

Generating Pseudo Search History Data in the Absence of Real Search History

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9828))

Abstract

Previous studies in Information Retrieval literature have shown that users’ search history can be leveraged to improve current search results. However sometimes we have little to no search history available. In such cases, it would be helpful to obtain data similar to search history data. One way of doing this is by simulating previous search interactions. In the present study, we focus on generating simulated “related queries” that can serve as an additional source of information about the current search [1]. Assuming that users reformulate their queries by leveraging some of the terms and key phrases they find in ranked documents during their search, we proposed simple models for generating such related queries.

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Author information

Authors and Affiliations

  1. Department of Computer Sciences, University of Delaware, Newark, DE, USA

    Ashraf Bah & Ben Carterette

Authors
  1. Ashraf Bah
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  2. Ben Carterette
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Corresponding author

Correspondence to Ashraf Bah .

Editor information

Editors and Affiliations

  1. Clausthal University of Technology, Clausthal-Zellerfeld, Germany

    Sven Hartmann

  2. Victoria University of Wellington, Wellington, New Zealand

    Hui Ma

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Bah, A., Carterette, B. (2016). Generating Pseudo Search History Data in the Absence of Real Search History. In: Hartmann, S., Ma, H. (eds) Database and Expert Systems Applications. DEXA 2016. Lecture Notes in Computer Science(), vol 9828. Springer, Cham. https://doi.org/10.1007/978-3-319-44406-2_34

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  • DOI: https://doi.org/10.1007/978-3-319-44406-2_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44405-5

  • Online ISBN: 978-3-319-44406-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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