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Enhancing access to scholarly publications with surrogate resources

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Abstract

Digital libraries containing scholarly publications are common today. They are an invaluable source of information to students, researchers, and practitioners. However, many digital libraries expose only the article metadata like title, author names, publication date, and the abstract for free; access to full-text requires access toll. Given that journal subscription charges are sometimes prohibitive, many important publications remain beyond the access of researchers, especially in developing countries. While open access publication solves this issue, the hard reality is that many research papers are not currently available for free reading or download. In this paper, we present a novel approach to alleviate this problem. We present a technique to retrieve open access surrogates of a scholarly article when the latter is unavailable freely in a digital library. Surrogates are articles semantically close to the original articles, written by the same author(s) and give valuable insights into the paper being searched for; they address the same or a very similar problem using the same or very similar techniques. Our focus on approximate matches of scholarly articles distinguishes our application from many academic search engines. We run it on a large corpus of computer science papers and compare the results with human judgment. Experimental results show that our tool can indeed identify relevant OA surrogates of access-restricted papers.

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Notes

  1. https://dl.acm.org.

  2. https://ieeexplore.ieee.org/Xplore/home.jsp.

  3. https://www.sciencedirect.com/.

  4. https://link.springer.com/.

  5. https://www.ndl.gov.in.

  6. https://www.inflibnet.ac.in/ess/index.php.

  7. https://www.research4life.org/.

  8. https://sci-hub.se/.

  9. https://arxiv.org/.

  10. https://www.researchgate.net/.

  11. https://www.academia.edu/.

  12. https://scholar.google.com.

  13. http://dev.www.isocdev.org/sites/default/files/07_1_1.pdf.

  14. https://academic.microsoft.com/.

  15. https://www.semanticscholar.org/.

  16. https://citeseerx.ist.psu.edu/.

  17. https://openaccessbutton.org/.

  18. https://openaccessbutton.org/about

  19. https://unpaywall.org/.

  20. https://blog.acolyer.org/.

  21. https://dblp.uni-trier.de/.

  22. https://scikit-learn.org/.

  23. https://radimrehurek.com/gensim/.

  24. https://github.com/zalandoresearch/flair.

  25. The OA links were manually verified on May 26, 2019.

  26. https://github.com/soumyaxyz/illumine/.

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Acknowledgements

This work is supported by National Digital Library of India Project sponsored by Ministry of Human Resource Development (Grant No. F.No.16-7/2017-TEL), Government of India at IIT Kharagpur. We thank Soumya Banerjee and Gopal Agarwal of the Department of Information Technology, Jadavpur University for their assistance in preparing the dataset used in this work.

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Authors and Affiliations

  1. National Digital Library of India, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    Debarshi Kumar Sanyal

  2. Center for Educational Technology, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    Plaban Kumar Bhowmick

  3. Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    Partha Pratim Das & T. Y. S. S. Santosh

  4. Department of Information Technology, Jadavpur University, Kolkata, 700098, India

    Samiran Chattopadhyay

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  1. Debarshi Kumar Sanyal
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  5. T. Y. S. S. Santosh
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Correspondence to Debarshi Kumar Sanyal.

Appendix

Appendix

This “Appendix” displays tables containing data and experimental results reported in the main text.

Table 1 Papers and their top-1 OA surrogates in the dataset
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Table 2 The top-1 OA surrogate that is dropped when TMIN is changed from 0.2 to 0.3
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Table 3 The top-1 OA surrogates that are dropped when TMIN is changed from 0.3 to 0.4
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Sanyal, D.K., Bhowmick, P.K., Das, P.P. et al. Enhancing access to scholarly publications with surrogate resources. Scientometrics 121, 1129–1164 (2019). https://doi.org/10.1007/s11192-019-03227-4

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