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

Author

Listed:
  • Chaker Jebari

    (University of Technology and Applied Sciences)

  • Enrique Herrera-Viedma

    (University of Granada)

  • Manuel Jesus Cobo

    (University of Granada)

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.

Suggested Citation

  • Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2023. "Context-aware citation recommendation of scientific papers: comparative study, gaps and trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4243-4268, August.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:8:d:10.1007_s11192-023-04773-8
    DOI: 10.1007/s11192-023-04773-8
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    References listed on IDEAS

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    1. Marc Bertin & Iana Atanassova & Yves Gingras & Vincent Larivière, 2016. "The invariant distribution of references in scientific articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(1), pages 164-177, January.
    2. Thelwall, Mike, 2019. "Should citations be counted separately from each originating section?," Journal of Informetrics, Elsevier, vol. 13(2), pages 658-678.
    3. Zafar Ali & Irfan Ullah & Amin Khan & Asim Ullah Jan & Khan Muhammad, 2021. "An overview and evaluation of citation recommendation models," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4083-4119, May.
    4. Zafar Ali & Irfan Ullah & Amin Ul Haq & Asim Ullah Jan & Khan Muhammad, 2021. "Correction to: An overview and evaluation of citation recommendation models," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8771-8771, October.
    5. Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2021. "The use of citation context to detect the evolution of research topics: a large-scale analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2971-2989, April.
    6. Saeed-Ul Hassan & Mubashir Imran & Sehrish Iqbal & Naif Radi Aljohani & Raheel Nawaz, 2018. "Deep context of citations using machine-learning models in scholarly full-text articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1645-1662, December.
    7. Henry Small, 2011. "Interpreting maps of science using citation context sentiments: a preliminary investigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 373-388, May.
    8. Shutian Ma & Chengzhi Zhang & Xiaozhong Liu, 2020. "A review of citation recommendation: from textual content to enriched context," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1445-1472, March.
    9. Chanwoo Jeong & Sion Jang & Eunjeong Park & Sungchul Choi, 2020. "A context-aware citation recommendation model with BERT and graph convolutional networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1907-1922, September.
    10. Xi Chen & Huan-jing Zhao & Shu Zhao & Jie Chen & Yan-ping Zhang, 2019. "Citation recommendation based on citation tendency," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 937-956, November.
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