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Context-aware citation recommendation of scientific papers: comparative study, gaps and trends

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Abstract

With the exponential increase in the number of published articles, recommending them on the basis of the citation context (also called local or citation-aware citation recommendation) has attracted many researchers in the last few years. Recently, some papers have been devoted to reviewing previous works about scientific paper recommendation. As far as can be discerned, none of the previous review papers has carried out an in-depth study to explain citation context and compare previous studies. This paper presents a comparative analysis of recent studies about context-aware citation recommendation. Moreover, four gaps related to citation context extraction, citation context classification, temporal and structural aspects of a citation context, and benchmarking datasets are identified. This comparative study can assist researchers interested in further exploring these four gaps.

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Notes

  1. https://dblp.org/statistics/index.html.

  2. https://github.com/knmnyn/ParsCit.

  3. https://scite.ai/

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Acknowledgements

This work has been supported by the Spanish State Research Agency through the project PID2019-105381 GA-I00 /AEI/10.13039/501100011033 (iScience).

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  1. Department of Information Technology, University of Technology and Applied Sciences, Ibri, Sultanate of Oman

    Chaker Jebari

  2. Department Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, 18071, Granada, Spain

    Enrique Herrera-Viedma & Manuel Jesus Cobo

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  1. Chaker Jebari
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Jebari, C., Herrera-Viedma, E. & Cobo, M.J. Context-aware citation recommendation of scientific papers: comparative study, gaps and trends. Scientometrics 128, 4243–4268 (2023). https://doi.org/10.1007/s11192-023-04773-8

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