Skip to main content
SpringerLink
Log in

Feature-Based Researcher Identification Framework Using Timeline Data

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Studies are actively ongoing for better understanding and strengthening the capabilities of researchers. To do so requires an accurate diagnosis and analysis of such researchers. Therefore, data of each researcher must be collected and be identified in a big-data environment. Consequently, researcher-name identification has emerged as an important issue. This paper proposes a framework for collecting, refining, identifying, and publicly offering researcher data. For identifying authors’ name, the proposed framework extracts timeline based patterns that make help to identify the same name authors with their representative attributes such as emails and affiliations. The results of the proposed framework based on timeline patterns, show a 69.5 % average author-identification rate given a group of otherwise unidentified authors.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Suber, P. (2007). Open access overview. Retrieved from Peter Suber’s website: http://www.earlham.edu/~peters/fos/overview.htm.

  2. Onte, M. B., & Marcial, D. E. (2013). Developing a web-based knowledge product outsourcing system at a university. Journal of Information Processing Systems, 9(4), 548–566.

    Article  Google Scholar 

  3. Song, S. K., Kim, D. J., Hwang, M., Kim, J., Jeong, D. H., Lee, S., & Sung, W. (2013). Prescriptive analytics system for improving research power. In 2013 IEEE 16th international conference on computational science and engineering (CSE) (pp. 1144–1145). IEEE.

  4. Lee, M., Cho, M., Gim, J., Jeong, D. H., & Jung, H. (2014). Prescriptive analytics system for scholar research performance enhancement. In International conference on human-computer interaction (pp. 186–190). Springer.

  5. Kumar, K. K., & Geethakumari, G. (2014). Detecting misinformation in online social networks using cognitive psychology. Human-centric Computing and Information Sciences, 4(1), 1.

    Article  Google Scholar 

  6. Ley, M. (2009). DBLP: some lessons learned. Proceedings of the VLDB Endowment, 2(2), 1493–1500.

    Article  MathSciNet  Google Scholar 

  7. Ley, M. (2002). The DBLP computer science bibliography: Evolution, research issues, perspectives. In International symposium on string processing and information retrieval (pp. 1–10). Springer, Berlin.

  8. Katsumata, M. (2014). Task context-aware e-mail platform for collaborative tasks. Human-centric Computing and Information Sciences, 4(1), 1.

    Article  Google Scholar 

  9. Minkov, E., Cohen, W. W., & Ng, A. Y. (2006). Contextual search and name disambiguation in email using graphs. In Proceedings of the 29th annual international ACM SIGIR conference on research and development in information retrieval (pp. 27–34). ACM.

  10. Smalheiser, N. R., & Torvik, V. I. (2009). Author name disambiguation. Annual review of information science and technology, 43(1), 1–43.

    Article  Google Scholar 

  11. Haak, L. L., Fenner, M., Paglione, L., Pentz, E., & Ratner, H. (2012). ORCID: A system to uniquely identify researchers. Learned Publishing, 25(4), 259–264.

    Article  Google Scholar 

  12. Wang, X., Tang, J., Cheng, H., & Philip, S. Y. (2011). Adana: Active name disambiguation. In 2011 IEEE 11th international conference on data mining (pp. 794–803). IEEE.

  13. Kang, I. S., Na, S. H., Lee, S., Jung, H., Kim, P., Sung, W. K., et al. (2009). On co-authorship for author disambiguation. Information Processing and Management, 45(1), 84–97.

    Article  Google Scholar 

  14. Li, L., Wang, H., Gao, H., & Li, J. (2010). EIF: A framework of effective entity identification. In International conference on web-age information management (pp. 717–728). Springer, Berlin.

  15. Maali, F., Cyganiak, R., & Peristeras, V. (2011). Re-using cool URIs: Entity reconciliation against LOD hubs. LDOW, 813.

  16. Ham, K. (2013). OpenRefine (version 2.5). http://openrefine.org. Free, open-source tool for cleaning and transforming data. Journal of the Medical Library Association: JMLA, 101(3), 233.

  17. Bizer, C., & Cyganiak, R. (2006). D2r server-publishing relational databases on the semantic web. In Poster at the 5th international semantic web conference (vol. 175).

  18. Gim, J., Jang, Y., Jeong, D. H., & Jung, H. (2014). Analyzing email patterns with timelines on researcher data. In 2014 3rd international workshop on semantic web-based computer intelligence with big-data (SWCIB workshop) (pp. 25–32).

  19. Bäumer, F. S., Gim, J., Jeong, D. H., Geierhos, M., & Jung, H. (2014). Linked open data system for scientific data sets. In IPaMin@ KONVENS.

  20. Almende, B. V. (2015). vis.js. http://visjs.org/.

Download references

Author information

Authors and Affiliations

  1. Korea Institute of Science and Technology Information (KISTI), 245 Daehak-ro, Yuseong-gu, Daejeon, 305-806, South Korea

    Jangwon Gim, Yunji Jang, Hanmin Jung & Do-Heon Jeong

  2. University of Science and Technology (UST), 217 Gajeong-ro, Yusong-gu, Daejeon, 305-350, South Korea

    Yunji Jang

Authors
  1. Jangwon Gim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yunji Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hanmin Jung
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Do-Heon Jeong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Do-Heon Jeong.

Ethics declarations

Conflict of Interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gim, J., Jang, Y., Jung, H. et al. Feature-Based Researcher Identification Framework Using Timeline Data. Wireless Pers Commun 91, 1653–1667 (2016). https://doi.org/10.1007/s11277-016-3662-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3662-5

Keywords

Search

Navigation