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Ethnicity Sensitive Author Disambiguation Using Semi-supervised Learning

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Knowledge Engineering and Semantic Web (KESW 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 649))

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Abstract

Building on more than one million crowdsourced annotations that we publicly release, we propose a new automated disambiguation solution exploiting this data (i) to learn an accurate classifier for identifying coreferring authors and (ii) to guide the clustering of scientific publications by distinct authors in a semi-supervised way. To the best of our knowledge, our analysis is the first to be carried out on data of this size and coverage. With respect to the state of the art, we validate the general pipeline used in most existing solutions, and improve by: (i) proposing new phonetic-based blocking strategies, thereby increasing recall; (ii) adding strong ethnicity-sensitive features for learning a linkage function, thereby tailoring disambiguation to non-Western author names whenever necessary; and (iii) showing the importance of balancing negative and positive examples when learning the linkage function.

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Notes

  1. 1.

    \((n,m)-\) TF-IDF vectors are TF-IDF vectors computed from n, \(n+1\), ..., m-grams.

  2. 2.

    https://github.com/inspirehep/beard.

  3. 3.

    https://github.com/glouppe/paper-author-disambiguation.

  4. 4.

    This holds for the data we extracted, but may in the future, with the rise of non-Western researchers, be an underestimate of the ambiguous cases.

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Author information

Authors and Affiliations

  1. CERN, Geneva, Switzerland

    Gilles Louppe & Eamonn James Maguire

  2. Univ Lyon, ISH, USR 3385, CNRS, and ERIC Lab, EA 3083, Lyon, France

    Hussein T. Al-Natsheh

  3. University of Warsaw, Warszawa, Poland

    Mateusz Susik

Authors
  1. Gilles Louppe
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  2. Hussein T. Al-Natsheh
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  3. Mateusz Susik
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  4. Eamonn James Maguire
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Corresponding author

Correspondence to Mateusz Susik .

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Editors and Affiliations

  1. Leipzig University , Leipzig, Germany

    Axel-Cyrille Ngonga Ngomo

  2. Czech Technical University in Prague , Praha, Czech Republic

    Petr Křemen

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Louppe, G., Al-Natsheh, H.T., Susik, M., Maguire, E.J. (2016). Ethnicity Sensitive Author Disambiguation Using Semi-supervised Learning. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_21

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  • DOI: https://doi.org/10.1007/978-3-319-45880-9_21

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