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Analyzing Mathematical Content for Plagiarism and Recommendations

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Advances in Information Retrieval (ECIR 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14612))

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Abstract

Defined as “the use of ideas, concepts, words, or structures without appropriately acknowledging the source to benefit in a setting where originality is expected" [6], plagiarism poses a severe concern in the rapidly increasing number of scientific publications.

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Acknowledgement

This work is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 437179652 and the Deutscher Akademischer Austauschdienst (DAAD, German Academic Exchange Service - 57515245).

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Authors and Affiliations

  1. Georg August University of Göttingen, Göttingen, Germany

    Ankit Satpute

  2. FIZ Karlsruhe Leibniz Institute for Information Infrastructure, Berlin, Germany

    Ankit Satpute

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  1. Ankit Satpute
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Correspondence to Ankit Satpute .

Editor information

Editors and Affiliations

  1. Georgetown University, Washington, WA, USA

    Nazli Goharian

  2. University of Pisa, PISA, Pisa, Italy

    Nicola Tonellotto

  3. King's College London, London, UK

    Yulan He

  4. University College London, London, UK

    Aldo Lipani

  5. University of Glasgow, Glasgow, UK

    Graham McDonald

  6. University of Glasgow, Glasgow, UK

    Craig Macdonald

  7. University of Glasgow, Glasgow, UK

    Iadh Ounis

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Satpute, A. (2024). Analyzing Mathematical Content for Plagiarism and Recommendations. In: Goharian, N., et al. Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14612. Springer, Cham. https://doi.org/10.1007/978-3-031-56069-9_42

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  • DOI: https://doi.org/10.1007/978-3-031-56069-9_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56068-2

  • Online ISBN: 978-3-031-56069-9

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