Skip to main content
SpringerLink
Log in

Towards Man/Machine Co-authoring of Advanced Analytics Reports Around Big Data Repositories

  • Conference paper
  • First Online:
Intelligent Human Computer Interaction (IHCI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13184))

Included in the following conference series:

  • 1448 Accesses

Abstract

This paper explores the problem of generating advanced analytical report for gaining sophisticated insight from massive databases by machine assistance. This study shows a model that takes a country-specific scientometric scientific research analysis report as a template and goes into a curated source database to generate a similar insightful report for other countries. The overall process consists of three key phases. The first phase is processing the template report for identifying the generalizable data elements. The second phase is extracting the elements for the selected country from a scholarly database. The third phase is re-assembling the high-level report for the new case. A case study on big data analysis is presented for Saudi Arabia scientific research publications. The generated co-authored report was evaluated by 10 human reviewers through assessing several criteria in the report, which achieved a satisfactory evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Batcha, M.S., Ahmad, M.: Publication trend in an Indian journal and a Pakistan journal: a comparative analysis using scientometric approach. arXiv preprint arXiv:2102.12914 (2021)

  2. Li, J., Goerlandt, F., Reniers, G.: An overview of scientometric mapping for the safety science community: Methods, tools, and framework. Saf. Sci. 134, 105093 (2021). https://doi.org/10.1016/j.ssci.2020.105093

    Article  Google Scholar 

  3. Derntl, M.: Basics of research paper writing and publishing. Int. J. Technol. Enhanced Learn. 6(2), 105–123 (2014)

    Article  Google Scholar 

  4. Astin, C., Harvey, C., Janusz, S.: Writing about science for publication. School Sci. Rev. 97(359), 30–38 (2015)

    Google Scholar 

  5. Labbé, C., Labbé, D.: Duplicate and fake publications in the scientific literature: how many SCIgen papers in computer science? Scientometrics 94(1), 379–396 (2013). https://doi.org/10.1007/s11192-012-0781-y

    Article  Google Scholar 

  6. Noh, Y., et al.: WIRE: An Automated Report Generation System using Topical and Temporal Summarization. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (2020). https://doi.org/10.1145/3397271.3401409]

  7. Gkatzia, D., Hastie, H.: An ensemble method for content selection for data-to-text systems. arXiv preprint arXiv:1506.02922 (2015)

  8. Maas, L., et al.: The Care2Report system: automated medical reporting as an integrated solution to reduce administrative burden in healthcare (2020)

    Google Scholar 

  9. Nguyen, T.V., Ho-Le, T.P., Le, U.V.: International collaboration in scientific research in Vietnam: an analysis of patterns and impact. Scientometrics 110(2), 1035–1051 (2016). https://doi.org/10.1007/s11192-016-2201-1

    Article  Google Scholar 

  10. Ayers, M.: Quick review of Microsoft academic. Issues Sci. Technol. Librariansh. 96 (2020)

    Google Scholar 

  11. Salatino, A.A., Mannocci, A., Osborne, F.: Detection, analysis, and prediction of research topics with scientific knowledge graphs. In: Manolopoulos, Y., Vergoulis, T. (eds.) Predicting the Dynamics of Research Impact, pp. 225–252. Springer, Heidelberg (2021). https://doi.org/10.1007/978-3-030-86668-6_11

    Chapter  Google Scholar 

  12. Platform, A.C., L’Esteve, R.C.: The Definitive Guide to Azure Data Engineering

    Google Scholar 

  13. Mazumdar, P., Agarwal, S., Banerjee, A.: Microsoft azure storage. In: Mazumdar, P., Agarwal, S., Banerjee, A. (eds.) Pro SQL Server on Microsoft Azure, pp. 35–52. Springer, Heidelberg (2016). https://doi.org/10.1007/978-1-4842-2083-2_3

    Chapter  Google Scholar 

  14. Ropinski, T.: Combining interactive exploration and search for navigating academic citation data. Ulm University (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Information Systems Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

    Amal Babour

  2. Department of Computer Science, Kent State University, Kent, OH, 44240, USA

    Javed Khan

Authors
  1. Amal Babour
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Javed Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amal Babour .

Editor information

Editors and Affiliations

  1. Kent State University, Kent, OH, USA

    Jong-Hoon Kim

  2. University of Tartu, Tartu, Estonia

    Madhusudan Singh

  3. Kent State University, Kent, OH, USA

    Javed Khan

  4. Indian Institute of Information Technology, Allahabad, India

    Uma Shanker Tiwary

  5. Massachusetts Institute of Technology, Cambridge, MA, USA

    Marigankar Sur

  6. Hankuk University of Foreign Studies, Seoul, Korea (Republic of)

    Dhananjay Singh

Appendix

Appendix

Please visit the following link: http://medianet.kent.edu/techreports/TR2021-09-01-ScientometricAnalysis/TR2021-09-01-ScientometricReport.html for supporting files, including the data elements definitions, the reviewed stenotype form, and the data elements values of the case study.

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Babour, A., Khan, J. (2022). Towards Man/Machine Co-authoring of Advanced Analytics Reports Around Big Data Repositories. In: Kim, JH., Singh, M., Khan, J., Tiwary, U.S., Sur, M., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2021. Lecture Notes in Computer Science, vol 13184. Springer, Cham. https://doi.org/10.1007/978-3-030-98404-5_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-98404-5_53

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-98403-8

  • Online ISBN: 978-3-030-98404-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation