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Scientific paper recommendation systems: a literature review of recent publications

  • International Journal on Digital Libraries
  • Cornell University
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128
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Abstract

Scientific writing builds upon already published papers. Manual identification of publications to read, cite or consider as related papers relies on a researcher’s ability to identify fitting keywords or initial papers from which a literature search can be started. The rapidly increasing amount of papers has called for automatic measures to find the desired relevant publications, so-called paper recommendation systems. As the number of publications increases so does the amount of paper recommendation systems. Former literature reviews focused on discussing the general landscape of approaches throughout the years and highlight the main directions. We refrain from this perspective, instead we only consider a comparatively small time frame but analyse it fully. In this literature review we discuss used methods, datasets, evaluations and open challenges encountered in all works first released between January 2019 and October 2021. The goal of this survey is to provide a comprehensive and complete overview of current paper recommendation systems.

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Publication details

DOI
10.1007/s00799-022-00339-w
arXiv
2201.00682
Semantic Scholar
8b3966ed1fd58991c993047cebe7f7154209859d
Document type
JournalArticle
Source
International Journal on Digital Libraries
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