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Towards a Semantic Search Engine for Scientific Articles

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Research and Advanced Technology for Digital Libraries (TPDL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10450))

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Abstract

Because of the data deluge in scientific publication, finding relevant information is getting harder and harder for researchers and readers. Building an enhanced scientific search engine by taking semantic relations into account poses a great challenge. As a starting point, semantic relations between keywords from scientific articles could be extracted in order to classify articles. This might help later in the process of browsing and searching for content in a meaningful scientific way. Indeed, by connecting keywords, the context of the article can be extracted. This paper aims to provide ideas to build such a smart search engine and describes the initial contributions towards achieving such an ambitious goal.

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Author information

Authors and Affiliations

  1. MIPS, University of Haute-Alsace, Mulhouse, France

    Bastien Latard, Jonathan Weber, Germain Forestier & Michel Hassenforder

  2. MDPI AG, Basel, Switzerland

    Bastien Latard

Authors
  1. Bastien Latard
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  2. Jonathan Weber
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  3. Germain Forestier
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  4. Michel Hassenforder
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Corresponding author

Correspondence to Bastien Latard .

Editor information

Editors and Affiliations

  1. Faculteit der Geesteswetenschappen, Universiteit van Amsterdam , Amsterdam, The Netherlands

    Jaap Kamps

  2. Library & Information Center, University of Patras , Patras, Greece

    Giannis Tsakonas

  3. Aristotle University of Thessaloniki , Thessaloniki, Greece

    Yannis Manolopoulos

  4. Civil Engineering, University of Thrace , Kimmeria, Greece

    Lazaros Iliadis

  5. Informatics, Ionian University , Kerkyra, Greece

    Ioannis Karydis

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Latard, B., Weber, J., Forestier, G., Hassenforder, M. (2017). Towards a Semantic Search Engine for Scientific Articles. In: Kamps, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L., Karydis, I. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2017. Lecture Notes in Computer Science(), vol 10450. Springer, Cham. https://doi.org/10.1007/978-3-319-67008-9_54

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  • DOI: https://doi.org/10.1007/978-3-319-67008-9_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67007-2

  • Online ISBN: 978-3-319-67008-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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