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Bibliometric-Enhanced Information Retrieval: 8th International BIR Workshop

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Advances in Information Retrieval (ECIR 2019)

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Abstract

The Bibliometric-enhanced Information Retrieval workshop series (BIR) at ECIR tackles issues related to academic search, at the crossroads between Information Retrieval and Bibliometrics. BIR is a hot topic investigated by both academia (e.g., ArnetMiner, CiteSeer\(^\chi \), DocEar) and the industry (e.g., Google Scholar, Microsoft Academic Search, Semantic Scholar). An 8th iteration of the one-day BIR workshop was held at ECIR 2019.

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Notes

  1. 1.

    Bibliometrics refers to the statistical analysis of the academic literature [20] and plays a key role in scientometrics: the quantitative study of science and innovation [9].

  2. 2.

    https://easychair.org.

  3. 3.

    http://irsg.bcs.org/informer/.

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Author information

Authors and Affiliations

  1. Computer Science Department, IRIT UMR 5505, University of Toulouse, Toulouse, France

    Guillaume Cabanac

  2. Institute for Research in Applicable Computing, University of Bedfordshire, Luton, UK

    Ingo Frommholz

  3. GESIS – Leibniz-Institute for the Social Sciences, Cologne, Germany

    Philipp Mayr

Authors
  1. Guillaume Cabanac
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  2. Ingo Frommholz
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  3. Philipp Mayr
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Corresponding author

Correspondence to Guillaume Cabanac .

Editor information

Editors and Affiliations

  1. University of Strathclyde, Glasgow, UK

    Leif Azzopardi

  2. Bauhaus Universität Weimar, Weimar, Germany

    Benno Stein

  3. Universität Duisburg-Essen, Duisburg, Germany

    Norbert Fuhr

  4. GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany

    Philipp Mayr

  5. Delft University of Technology, Delft, The Netherlands

    Claudia Hauff

  6. University of Twente, Enschede, The Netherlands

    Djoerd Hiemstra

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Cabanac, G., Frommholz, I., Mayr, P. (2019). Bibliometric-Enhanced Information Retrieval: 8th International BIR Workshop. In: Azzopardi, L., Stein, B., Fuhr, N., Mayr, P., Hauff, C., Hiemstra, D. (eds) Advances in Information Retrieval. ECIR 2019. Lecture Notes in Computer Science(), vol 11438. Springer, Cham. https://doi.org/10.1007/978-3-030-15719-7_55

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  • DOI: https://doi.org/10.1007/978-3-030-15719-7_55

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  • Online ISBN: 978-3-030-15719-7

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