IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v122y2020i1d10.1007_s11192-019-03261-2.html
   My bibliography  Save this article

An efficient ontology-based topic-specific article recommendation model for best-fit reviewers

Author

Listed:
  • Gohar Rehman Chughtai

    (Chongqing University)

  • Jia Lee

    (Chongqing University)

  • Mahnoor Shahzadi

    (University of Electronic Science and Technology)

  • Asif Kabir

    (Kotli University)

  • Muhammad Arshad Shehzad Hassan

    (Chongqing University)

Abstract

In general peer review is accredited as the vital and utmost cornerstone of the scientific publishing and research developments. Undeniably, the reviewers play a decisive role in ensuring the qualitative scientific developments published in any venue (Journals, conferences). The conventional time-tested method of double-blind peer review has been criticized having the flaws of inability to find the novelty, paucity of clarity, paucity of soundness, prone to be biased, the paucity of impartiality, discrepancies amongst reviewers, the paucity of acknowledgment and inspiration to reviewers. In order to cope with some of its flaws and to ensure the excellence of peer review, it is indispensable to delve into the process of article recommendation to the best fit reviewers. Typically, this recommendation is done by the human expert, so less accurate as the manual recommendation is incapable of initial scrutinizing of the tome of articles submitted and best fitting reviewer’s profile. This work proposes ontology and topic-specific personalized recommendation system to recommend the articles to the best-fit reviewers. In this proposed ontology-based model, latent semantic analysis and entropy have been deployed for similarity measure and topic-specificity indicator, thus to fetch the information of the best-fitted reviewer’s profile. In this work, an experimental arrangement has been set up relying on the primary dataset related to the reviewer’s profile and article reviewed. Results show the feasibility of the proposed model and the correlational relationship between the semantics and the topic-specificity of the articles which could be adopted as an automatic article recommendation to best fitting reviewers.

Suggested Citation

  • Gohar Rehman Chughtai & Jia Lee & Mahnoor Shahzadi & Asif Kabir & Muhammad Arshad Shehzad Hassan, 2020. "An efficient ontology-based topic-specific article recommendation model for best-fit reviewers," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 249-265, January.
  • Handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03261-2
    DOI: 10.1007/s11192-019-03261-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03261-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-019-03261-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    2. Vrana, Scott R. & Vrana, Dylan T. & Penner, Louis A. & Eggly, Susan & Slatcher, Richard B. & Hagiwara, Nao, 2018. "Latent Semantic Analysis: A new measure of patient-physician communication," Social Science & Medicine, Elsevier, vol. 198(C), pages 22-26.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bastian Schaefermeier & Gerd Stumme & Tom Hanika, 2021. "Topic space trajectories," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5759-5795, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vîiu, Gabriel-Alexandru, 2016. "A theoretical evaluation of Hirsch-type bibliometric indicators confronted with extreme self-citation," Journal of Informetrics, Elsevier, vol. 10(2), pages 552-566.
    2. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    3. Aurelia Magdalena Pisoschi & Claudia Gabriela Pisoschi, 2016. "Is open access the solution to increase the impact of scientific journals?," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1075-1095, November.
    4. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    5. Kaur, Jasleen & Radicchi, Filippo & Menczer, Filippo, 2013. "Universality of scholarly impact metrics," Journal of Informetrics, Elsevier, vol. 7(4), pages 924-932.
    6. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    7. R. Karpagam & S. Gopalakrishnan & M. Natarajan & B. Ramesh Babu, 2011. "Mapping of nanoscience and nanotechnology research in India: a scientometric analysis, 1990–2009," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 501-522, November.
    8. David L. Anderson & John Tressler, 2013. "The Relevance of the “h-” and “g-” Index to Economics in the Context of A Nation-Wide Research Evaluation Scheme: The New Zealand Case," Economic Papers, The Economic Society of Australia, vol. 32(1), pages 81-94, March.
    9. Ash Mohammad Abbas, 2011. "Weighted indices for evaluating the quality of research with multiple authorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 107-131, July.
    10. Michael Zhang, 2021. "Announcement of Retraction," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(12), pages 1-14, December.
    11. Richard S. J. Tol, 2009. "The h-index and its alternatives: An application to the 100 most prolific economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(2), pages 317-324, August.
    12. Soutar, Geoffrey N. & Murphy, Jamie, 2009. "Journal quality: A Google Scholar analysis," Australasian marketing journal, Elsevier, vol. 17(3), pages 150-153.
    13. Thor, Andreas & Marx, Werner & Leydesdorff, Loet & Bornmann, Lutz, 2016. "Introducing CitedReferencesExplorer (CRExplorer): A program for reference publication year spectroscopy with cited references standardization," Journal of Informetrics, Elsevier, vol. 10(2), pages 503-515.
    14. Fan Li & Hao Zhou & De-Sheng Huang & Peng Guan, 2020. "Global Research Output and Theme Trends on Climate Change and Infectious Diseases: A Restrospective Bibliometric and Co-Word Biclustering Investigation of Papers Indexed in PubMed (1999–2018)," IJERPH, MDPI, vol. 17(14), pages 1-14, July.
    15. Perc, Matjaž, 2010. "Zipf’s law and log-normal distributions in measures of scientific output across fields and institutions: 40 years of Slovenia’s research as an example," Journal of Informetrics, Elsevier, vol. 4(3), pages 358-364.
    16. Nadeem Shafique Butt & Ahmad Azam Malik & Muhammad Qaiser Shahbaz, 2021. "Bibliometric Analysis of Statistics Journals Indexed in Web of Science Under Emerging Source Citation Index," SAGE Open, , vol. 11(1), pages 21582440209, January.
    17. L. Egghe, 2011. "The single publication H-index of papers in the Hirsch-core of a researcher and the indirect H-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 727-739, December.
    18. Christoph Bartneck & Servaas Kokkelmans, 2011. "Detecting h-index manipulation through self-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(1), pages 85-98, April.
    19. Aniruddha Maiti & Sai Shi & Slobodan Vucetic, 2023. "An ablation study on the use of publication venue quality to rank computer science departments," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4197-4218, August.
    20. Lathabai, Hiran H., 2020. "ψ-index: A new overall productivity index for actors of science and technology," Journal of Informetrics, Elsevier, vol. 14(4).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03261-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.